From ace1ce36576ef9d832a6b70c7198baa556a227f9 Mon Sep 17 00:00:00 2001 From: Sami Boukortt Date: Mon, 5 Feb 2024 16:42:22 +0100 Subject: [PATCH] Open-source the rest of the codebase --- .gitmodules | 3 + CMakeLists.txt | 23 ++ README.md | 51 ++- classd_simu/delta_sigma_quantizer.py | 143 +++++++++ classd_simu/quantizer.py | 186 +++++++++++ driver_model/driver_model.cc | 244 ++++++++++++++ driver_model/driver_model.py | 121 +++++++ optimizer/simplex_fork | 226 +++++++++++++ speaker_experiments/angular.cc | 219 +++++++++++++ speaker_experiments/audio_closed_loop | 157 +++++++++ speaker_experiments/emphasizer.cc | 352 +++++++++++++++++++++ speaker_experiments/revolve.cc | 300 ++++++++++++++++++ speaker_experiments/spectrum_similarity.cc | 251 +++++++++++++++ speaker_experiments/two_to_three.cc | 144 +++++++++ speaker_experiments/virtual_speakers.cc | 160 ++++++++++ testdata/a.wav | Bin 0 -> 39246 bytes testdata/silph31.wav | Bin 0 -> 410168 bytes third_party/absl | 1 + 18 files changed, 2573 insertions(+), 8 deletions(-) create mode 100644 .gitmodules create mode 100644 CMakeLists.txt create mode 100644 classd_simu/delta_sigma_quantizer.py create mode 100644 classd_simu/quantizer.py create mode 100644 driver_model/driver_model.cc create mode 100644 driver_model/driver_model.py create mode 100755 optimizer/simplex_fork create mode 100644 speaker_experiments/angular.cc create mode 100755 speaker_experiments/audio_closed_loop create mode 100644 speaker_experiments/emphasizer.cc create mode 100644 speaker_experiments/revolve.cc create mode 100644 speaker_experiments/spectrum_similarity.cc create mode 100644 speaker_experiments/two_to_three.cc create mode 100644 speaker_experiments/virtual_speakers.cc create mode 100644 testdata/a.wav create mode 100644 testdata/silph31.wav create mode 160000 third_party/absl diff --git a/.gitmodules b/.gitmodules new file mode 100644 index 0000000..0c7561d --- /dev/null +++ b/.gitmodules @@ -0,0 +1,3 @@ +[submodule "third_party/absl"] + path = third_party/absl + url = https://github.com/abseil/abseil-cpp.git diff --git a/CMakeLists.txt b/CMakeLists.txt new file mode 100644 index 0000000..21dfe19 --- /dev/null +++ b/CMakeLists.txt @@ -0,0 +1,23 @@ +cmake_minimum_required(VERSION 3.10) + +project(Tabuli CXX) + +find_package(PkgConfig REQUIRED) +pkg_check_modules(SndFile REQUIRED IMPORTED_TARGET sndfile) +pkg_check_modules(FFTW3 REQUIRED IMPORTED_TARGET fftw3f) +find_package(Eigen3 REQUIRED) +add_subdirectory(third_party/absl) + +add_executable(driver_model driver_model/driver_model.cc) +target_link_libraries(driver_model PkgConfig::SndFile) + +foreach (experiment IN ITEMS angular emphasizer revolve spectrum_similarity two_to_three virtual_speakers) + add_executable(${experiment} speaker_experiments/${experiment}.cc) + target_link_libraries(${experiment} PkgConfig::SndFile absl::flags absl::flags_parse absl::log absl::log_internal_check_impl) +endforeach () + +target_link_libraries(angular PkgConfig::FFTW3) +target_link_libraries(spectrum_similarity PkgConfig::FFTW3) +target_link_libraries(two_to_three PkgConfig::FFTW3) + +target_link_libraries(virtual_speakers Eigen3::Eigen) diff --git a/README.md b/README.md index 2c7433d..241ccd4 100644 --- a/README.md +++ b/README.md @@ -1,12 +1,47 @@ -### Overview +Tabuli is a project for [Wave field synthesis](https://en.wikipedia.org/wiki/Wave_field_synthesis). -Tabuli is a project for Wave field synthesis. +This project is a study about upmixing 2-channel stereo input audio streams into +multi-channel (e.g. 16 channel) wave field speaker use. -The project relates to Wave field synthesis hardware simulations, -machine learning models, and other simulations. +We produce wave the field synthesis audio using an multi-stage process. The +states are reverbration separation, dry sound spatial location, rereverbration, +rendering, and speaker reverse physics modeling. The different stages produce +wav-files that are compatible with sox as an auxilliary processing tool that can +be applied for input, output or intermediate results of the stages. -This is a highly experimental research project at this stage. +The first step makes an attempt to separate the input stereo audio into three +stereo audio streams that together sum back into the input stereo. The first of +them attempts to capture the 'dry' audio of the recording, without reverbration +and with minimal in-instrument resonances. The second stream will contain some +early room reverbration and most of the in-instrument resonances. +The third stream will contain the sound that has longer reverb within the room +or concert hall, i.e., late reverb. The separation happens in a module called +'emphasizer'. -Top level folders roughly outline the area of research / applicability. -Inside those sub-folders denote sub-projects and usually have `_v#` (version) -suffix to make it easier to track approach changes / fundamental redesigns. +In the dry sound spatial location, we use a process that reverses the predicted +amplitudes of a spatialized source and tries to finds an optimal single source +for each frequency band to explain a microphone sensitivity pattern that we +define. In the current practical application we use this process to upmix the +audio from two tracks to twelwe tracks, but we could use a larger or smaller +number of tracks in upmixing. We call this model 'angular' as it relates to +computing the angle of the sound source. + +In the rereverbration we attempt to produce a multi-dimensional model of the +reverbration based on the position of the dry sounds, while maintaining the +volume of the reverbration within the two measured stages of reverbration -- the +early and late reverbration. + +In the rendering phase of the computation, a 3d-geometric virtual placement of +sound sources (often a linear array) is rendered to actual speakers, such as a +wave field speaker. Often it is practical to keep the virtual speakers a bit +further away from the listener than the actual linear array, as that will allow +the speakers to collaborate rather than trying to reproduce complex +interferences. + +The last phase of computation, that we call 'driver model', will apply the +inverse physics of speaker drivers. This may allow us to reduce the impact of +various non-linearities and oscillations within the speaker driver and +contribute to the overall experience positively. + +Contact Jyrki Alakuijala (jyrki@google.com) for more information about this +project. diff --git a/classd_simu/delta_sigma_quantizer.py b/classd_simu/delta_sigma_quantizer.py new file mode 100644 index 0000000..e5b1a37 --- /dev/null +++ b/classd_simu/delta_sigma_quantizer.py @@ -0,0 +1,143 @@ +# Copyright 2024 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Quantizer - dequantizer script.""" +# Quantizes the input signal with 1 bit using delta-sigma modulation and +# dequantizes using a leaky integrator capacitor low pass filter. + +import numpy +import scipy.io.wavfile +import scipy.signal + +_OVERSAMPLE = 32 + + +def rmse(original, reproduction): + """Calculates RMSE (root mean square error) between original and reproduction. + + Args: + original: Original signal (must be array-like). + reproduction: Reproduced signal after quntization and dequantization (must + be array-like). + + Returns: + A scalar RMSE between original and reproduction. + """ + return numpy.sqrt( + numpy.mean((numpy.asarray(original) - numpy.asarray(reproduction))**2)) + + +def quantize_delta_sigma(sig): + """Quantizes sig using 1 bit delta-sigma modulation of second order. + + Args: + sig: Signal to be quantized + + Returns: + The binary output of the 1 bit delta sigma modulator + """ + # Initialize result array + result = numpy.zeros(len(sig) * _OVERSAMPLE) + + # Make sure we have an array + sig = numpy.asarray(sig) + + # Upsample the signal with linear interpolation + + # Indices on which we will calculate interpolated values + x = numpy.arange(len(sig) * _OVERSAMPLE) + # Indices on which we have known values (multiples of _OVERSAMPLE) + xp = numpy.arange(len(sig)) * _OVERSAMPLE + signal_ovs = numpy.interp(x, xp, sig) + + # Possible quantizer outputs. + d_minus_plus = (-1 << 15, 1<<15) + + integrator = 0 + integrator2 = 0 + + for i in range(len(signal_ovs)): + integrator += signal_ovs[i] + integrator2_prev = integrator2 + + # If integrator is over the threshold, decrease by D and add a pulse to + # the output + # Otherwise if it is not above the threshold add D and add a negative pulse. + delta = d_minus_plus[integrator2_prev > 0] + result[i] = delta + integrator -= delta + integrator2 -= delta + + integrator2 += integrator + + return result + + +def dequantize_delta_sigma(signal): + """Dequantizes the binary output of the delta sigma modulator. + + Uses a low pass filter with leaky integrators. + + Args: + signal: Signal to be dequantized + + Returns: + The dequantized signal + """ + retval = numpy.zeros(len(signal) // _OVERSAMPLE) + integrator = 0 + integrator2 = 0 + integrator3 = 0 + k = 0.15 + k2 = k + k3 = k + kc = 1.0 - k + k2c = 1.0 - k2 + k3c = 1.0 - k3 + + # The following loop is implementing the filter of integrators using + # arithmetic operations and reassignments. A better solution could describe + # the integrators as LTI filters, and calculate their outputs by multiplying + # the fourier transform of the input signal and the frequency response of the + # integrator. IFFT of this product wields the desired output. + # We keep the implementation as is because we want it to correspond to what is + # going to happen in assembly. + period = 0 + for i, v in enumerate(signal): + integrator = integrator * kc + k * v + integrator2 = integrator2 * k2c + k2 * integrator + integrator3 = integrator3 * k3c + k3 * integrator2 + + period += integrator3 + if not (i+1) % _OVERSAMPLE: + retval[(i+1) // _OVERSAMPLE - 1] = period / _OVERSAMPLE + period = 0 + return retval + + +def demo(): + """Demo that quantizes and dequantizes an audio signal. + """ + fname = './../testdata/a.wav' + rate, data = scipy.io.wavfile.read(fname) + print('RMS value of signal: ', rmse(data, numpy.zeros(len(data)))) + + result_quant = quantize_delta_sigma(data) + result = dequantize_delta_sigma(result_quant) + min_length = min(len(data), len(result)) + trimmed_data = data[:min_length] + trimmed_result = result[:min_length] + + print('RMS error: ', rmse(trimmed_data, trimmed_result)) + scipy.io.wavfile.write('result.wav', rate, result.astype(numpy.int16)) diff --git a/classd_simu/quantizer.py b/classd_simu/quantizer.py new file mode 100644 index 0000000..42f56ba --- /dev/null +++ b/classd_simu/quantizer.py @@ -0,0 +1,186 @@ +# Copyright 2024 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Quantizer - dequantizer script.""" +# Quantizes the input signal with 1 bit and dequantizes using leaky integrator +# capacitors. +import sys + +import numpy +import scipy.io.wavfile + +_OVERSAMPLE = 32 + + +def rmse(original, reproduction): + """Calculates RMSE (root mean square error) between original and reproduction. + + Args: + original: Original signal (must be array-like). + reproduction: Reproduced signal after quntization and dequantization (must + be array-like). + + Returns: + A scalar RMSE between original and reproduction. + """ + return numpy.sqrt( + numpy.mean((numpy.asarray(original) - numpy.asarray(reproduction))**2)) + + +def quantize(signal): + """Quantizes an audio signal with 1 bit. + + Args: + signal: Signal to be quantized. + + Returns: + A list containing the quantized signal samples. + """ + retval = [] + bit15 = 1 << 15 + error = 0 + for i in range(len(signal) - 1): + # We sharpen the signal with a filter that amplifies high frequencies, + # because quantization with 1 bit will attenuate them. + extrapolated_v = 3 * signal[i] - 2 * signal[i + 1] + + # We repeat _OVERSAMPLE times for every sample of the extrapolated signal. + # This aims at reducing quantization noise power. + for _ in range(_OVERSAMPLE): + inp = extrapolated_v + error + out = bit15 if inp >= 0 else -bit15 + error = inp - out + retval.append(out) + + # Append _OVERSAMPLE extra values to result so that its size is + # len(signal) * _OVERSAMPLE + inp = signal[len(signal) - 1] + out = bit15 if inp >= 0 else -bit15 + retval.extend([out] * _OVERSAMPLE) + return retval + + +def dequantize(signal): + """Dequantizes using a filter of 3 leaky integrator capacitors. + + Each integrator with constant k acts as an LTI filter with impulse response + k*(1-k)**n. The three integrators are cascaded. The dequantized + signal is derived by the output of the third integrator by averaging every + _OVERSAMPLE samples. + + Args: + signal: Signal to be dequantized. + + Returns: + a list containing the samples of the dequantized signal. + """ + retval = [] + integrator = 0 + integrator2 = 0 + integrator3 = 0 + k = 0.0253 + k2 = k + k3 = k + + # The following loop is implementing the filter of integrators using + # arithmetic operations and reassignments. A better solution could describe + # the integrators as LTI filters, and calculate their outputs by multiplying + # the fourier transform of the input signal and the frequency response of the + # integrator. IFFT of this product wields the desired output. + # We keep the implementation as is because we want it to correspond to what is + # going to happen in assembly. + period = 0 + for i, v in enumerate(signal): + integrator = integrator * (1.0 - k) + k * v + integrator2 = integrator2 * (1.0 - k2) + k2 * integrator + integrator3 = integrator3 * (1.0 - k3) + k3 * integrator2 + period += integrator3 + if i & (_OVERSAMPLE - 1) == _OVERSAMPLE - 1: + retval.append(period / _OVERSAMPLE) + period = 0 + return retval + + +def reduce_frequency(signal): + """Regroups 0's and 1's together in fixed size windows of the signal. + + Args: + signal: Signal to be reordered in windows. + + Returns: + a list containing the samples of the reordered signal. + """ + # TODO(tseligas): If window_length == _OVERSAMPLING we can try doing + # quantization and grouping in one step. + window_length = 32 + + # We are padding the signal with zeros to make its length a multiple of + # window_length + signal = numpy.asarray(signal) + target_length = -(-signal.size // window_length) * window_length + padded_signal = numpy.pad(signal, [(0, target_length - signal.size)]) + + windowed_signal = padded_signal.reshape(-1, window_length) + bit15 = 1 << 15 + + return numpy.ravel(numpy.where( + numpy.arange(windowed_signal.shape[-1])[numpy.newaxis, :] < + (windowed_signal == -bit15).sum(axis=-1, keepdims=True), -bit15, bit15)) + + +def demo(): + """Demo that reads and processes an audio signal. + + It quantizes with 1 bit and dequantizes using a triple integrator filter. + It iteratively shifts the quantized signal to the left in order to find + the offset that minimizes RMSE (root mean square error). + Finally it groups together the logical low and high values in windows of + the quantized signal to reduce high frequency components. + """ + fname = './../testdata/a.wav' + rate, data = scipy.io.wavfile.read(fname) + + result_quant = quantize(data) + result = numpy.array(dequantize(result_quant)) + + print('Rmse is: ' + str(rmse(data, result))) + + scipy.io.wavfile.write('result.wav', rate, result.astype(numpy.int16)) + + # Shift the quantized signal to the left in order to find the offset that + # minimizes rmse + min_rmse = sys.float_info.max + min_offset = 0 + for offset in range(150): + offset_result = numpy.roll(result_quant, -offset) + curr_rmse = rmse(data, numpy.array(dequantize(offset_result))) + print('iteration: ' + str(offset) + ' with rmse: ' + str(curr_rmse)) + if curr_rmse < min_rmse: + min_rmse = curr_rmse + min_offset = offset + + result_min_rmse = numpy.roll(result, -min_offset) + print('Offset that minimizes rmse is: ' + str(min_offset)) + print('Minimumm rmse is: ' + str(min_rmse)) + + scipy.io.wavfile.write('result_min_rmse.wav', rate, + result_min_rmse.astype(numpy.int16)) + + result_quant_reduced = reduce_frequency(result_quant) + result_reduced = dequantize(result_quant_reduced) + + print('RMSE of signal with frequency reduction: ' + + str(rmse(data, numpy.array(result_reduced[0:len(data)])))) + scipy.io.wavfile.write('result_reduced.wav', rate, + numpy.array(result_reduced).astype(numpy.int16)) diff --git a/driver_model/driver_model.cc b/driver_model/driver_model.cc new file mode 100644 index 0000000..681d62d --- /dev/null +++ b/driver_model/driver_model.cc @@ -0,0 +1,244 @@ +// Copyright 2024 Google LLC +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// https://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +/* +This utility is intended to improve the driver dynamics of a wave +field synthesis loudspeaker prototype currently located on Jyrki's desk. + +This utility works best with 48k sample rate. +*/ + +#include +#include + +#include +#include +#include +#include + +struct Sound { + public: + std::vector wav; + int numsamples; + int numchannels; + int samplerate; +}; + +void Read(const std::string &path, Sound *snd) { + SndfileHandle f(path); + if (!f) { + fprintf(stderr, "%s\n", f.strError()); + exit(-1); + } + int numchannels = f.channels(); + snd->numchannels = numchannels; + snd->samplerate = f.samplerate(); + int numsamples = f.frames(); + snd->numsamples = numsamples; + snd->wav.resize(numchannels * numsamples); + + printf("read %d channels, %d samples: size()=%zu\n", numchannels, numsamples, + snd->wav.size()); + if (f.readf(snd->wav.data(), numsamples) != numsamples) { + fprintf(stderr, "%s\n", f.strError()); + exit(-1); + } +} + +void Write(const std::string &path, const Sound &snd) { + int numsamples = snd.numsamples; + int numchannels = snd.numchannels; + int samplerate = snd.samplerate; + printf("write %d channels, %d samples\n", numchannels, numsamples); + SndfileHandle f(path, /*mode=*/SFM_WRITE, + /*format=*/SF_FORMAT_WAV | SF_FORMAT_PCM_24, + /*channels=*/numchannels, /*samplerate=*/samplerate); + f.writef(snd.wav.data(), snd.numsamples); +} + +void DriverModel(int n, float *p, int stride) { + float dpos = 0.0; + float pos = 0.0; + + const float kSuspension = 0.00039; + + // damping reduces the speed of the membrane passively as it + // emits energy or converts it to heat in the suspension deformations + const float damping = 0.99999; + + float hysteresis = 0; + const float hysteresis_damping = 0.93; + const float force_to_hysteresis = 3e-4; + float min_hys = 99; + float max_hys = -99; + + // Heat in the coil increases resistance. + float coil_heat = 0; + const float coil_cooling = 0.9997; + const float coil_heat_mul = 3e-7; + float max_heat = 0; + + // Magnetic field gets weaker when the coil is displaced. + // const float displacement_mul = 1e-35; + + const float kInputMul = 0.3; + const float kSharpen = 0.01; + const float kInputMulCenter = kInputMul * (1.0 + 2 * kSharpen); + const float kInputMulOff = -kInputMul * kSharpen; + + for (int i = 0; i < n; i += stride) { + float force = 0; + if (i < n - 2 * stride - 1) { + force = (kInputMulOff * (p[i + 2 * stride] + p[i]) + + kInputMulCenter * p[i + stride]); + } + + float v = force; + for (int k = 0; k < 4; ++k) { + dpos *= damping; + dpos += 0.25 * force; + pos += 0.25 * dpos; + v += 0.25 * kSuspension * pos; + pos *= 0.99999; + } + + coil_heat += v * v; + coil_heat *= coil_cooling; + + hysteresis += force_to_hysteresis * v; + hysteresis *= hysteresis_damping; + + min_hys = std::min(min_hys, hysteresis); + max_hys = std::max(max_hys, hysteresis); + // hysteresis = min(max(hysteresis, -0.005), 0.005) + + max_heat = std::max(max_heat, coil_heat); + v *= 1.0 - hysteresis; + v *= 1.0 + coil_heat * coil_heat_mul; + // v *= 1.0 + 0.0 * displacement_mul * pow(pos, 4); + // printf("%d/%d: %g -> %g\n", i, n, p[i], v); + p[i] = v; + } + printf("hys: %g %g heat: %g\n", min_hys, max_hys, coil_heat_mul * max_heat); +} + +#include +#include + +void BlockFilter(int n, const float *from, float *to, int stride, int sigma) { + double sum = 0; + int i = 0; + float mul = 1.0 / (1 + 2 * sigma); + for (i = -stride * sigma; i < n; i += stride) { + if (i < n - sigma * stride) { + sum += from[i + sigma * stride]; + } + if (i >= 0) { + to[i] = sum * mul; + } + if (i >= sigma * stride) { + sum -= from[i - sigma * stride]; + } + } +} + +bool SkipChannel(int c, const Sound &snd) { + return snd.numchannels == 20 && (c == 0 || c == 1 || c == 10 || c == 11); +} + +// Reduce the lowest frequencies so that we don't run into +// problems with too low frequencies. +void HighPass20Hz(Sound &snd, int len) { + Sound buf0 = snd; + Sound buf1 = snd; + for (int c = 0; c < snd.numchannels; ++c) { + if (SkipChannel(c, snd)) continue; + fprintf(stderr, "high pass %d\n", c); + BlockFilter(snd.wav.size(), &buf0.wav[c], &buf1.wav[c], snd.numchannels, + len); + BlockFilter(snd.wav.size(), &buf1.wav[c], &buf0.wav[c], snd.numchannels, + len); + BlockFilter(snd.wav.size(), &buf0.wav[c], &buf1.wav[c], snd.numchannels, + len); + } + for (int i = 0; i < snd.wav.size(); ++i) { + snd.wav[i] -= buf1.wav[i]; + } +} + +bool FrontChannel(int c) { return c >= 4 && c != 10 && c != 11 && c < 18; } + +// We cannot locate bass, so we can make it mono first to reduce +// the maximum amount placed on any speaker. +void MakeMonoLowPass80Hz(Sound &snd, int len) { + Sound buf0 = snd; + Sound buf1 = snd; + for (int c = 0; c < snd.numchannels; ++c) { + if (SkipChannel(c, snd)) continue; + fprintf(stderr, "mono low pass %d\n", c); + BlockFilter(snd.wav.size(), &buf0.wav[c], &buf1.wav[c], snd.numchannels, + len); + BlockFilter(snd.wav.size(), &buf1.wav[c], &buf0.wav[c], snd.numchannels, + len); + BlockFilter(snd.wav.size(), &buf0.wav[c], &buf1.wav[c], snd.numchannels, + len); + } + // Remove the individual bass tracks. + for (int i = 0; i < buf1.wav.size(); i += buf1.numchannels) { + for (int c = 0; c < buf1.numchannels; ++c) { + if (SkipChannel(c, snd)) continue; + snd.wav[i + c] -= buf1.wav[i + c]; + } + } + // Mono bass track on 0th track on buf1. Gather it only + // from front tracks. + for (int i = 0; i < buf1.wav.size(); i += buf1.numchannels) { + for (int c = 1; c < buf1.numchannels; ++c) { + if (!FrontChannel(c)) continue; + buf1.wav[i] += buf1.wav[i + c]; + } + buf1.wav[i] *= 1 / 16.; // ... but add it to all 16 channels. + } + for (int i = 0; i < snd.wav.size(); i += snd.numchannels) { + for (int c = 0; c < snd.numchannels; ++c) { + if (SkipChannel(c, snd)) continue; + if (i > 0) { + snd.wav[i + c] += buf1.wav[i]; // Add mono bass on all tracks. + } + } + } +} + +int main(int argc, char **argv) { + if (argc != 3) { + fprintf(stderr, + "Usage: %s in.wav out.wav\n" + "Only 32 bit float tracks [sox -e float -b 32] are supported\n", + argv[0]); + exit(1); + } + const char *wav_in = argv[1]; + const char *wav_out = argv[2]; + Sound snd; + Read(wav_in, &snd); + HighPass20Hz(snd, 400); + MakeMonoLowPass80Hz(snd, 250); + for (int c = 0; c < snd.numchannels; ++c) { + if (SkipChannel(c, snd)) continue; + fprintf(stderr, "processing channel %d\n", c); + DriverModel(snd.wav.size(), &snd.wav[c], snd.numchannels); + } + Write(wav_out, snd); + return 0; +} diff --git a/driver_model/driver_model.py b/driver_model/driver_model.py new file mode 100644 index 0000000..5fee14c --- /dev/null +++ b/driver_model/driver_model.py @@ -0,0 +1,121 @@ +# Copyright 2024 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Explorative code for studying loudspeaker physics. + +This is not a software component to be used in larger engineering +designs as-is. + +This algorithm will likely be integrated in +speaker_experiments/virtual_speakers in C++. +""" + + +import numpy +import scipy +import scipy.io +import scipy.io.wavfile +import scipy.ndimage + + +# Read the wave using scipy + +samplerate, input_wav = scipy.io.wavfile.read('/tmp/1.wav') +input_wav = input_wav.astype(float) +#input_wav *= 1/32768 # 32 bit samples need scaling down + +def fade(wav): + for i in range(min(10000, len(wav))): + mul = 1.0 - i / 10000.; + wav[wav.shape[0] - i - 1][0] = 0 + wav[wav.shape[0] - i - 1][1] = 0 + +fade(input_wav) +print(input_wav.shape[0]) + +print("gaussian") +#blurred = scipy.ndimage.gaussian_filter1d(input_wav, 330.0, 0, 0) +#input_wav -= blurred +blurred = scipy.ndimage.gaussian_filter1d(input_wav, 440.0, 0, 0) +input_wav -= blurred +print("end gaussian") + + +output = numpy.zeros(input_wav.shape) + +# parameters +# suspension strength is basically a correction level multiplier +suspension = 0.00034 + +# damping reduces the speed of the membrane passively as it +# emits energy or converts it to heat in the suspension deformations +damping = 0.99975 + +currpow = 0.0 + +hysteresis = 0 +hysteresis_damping = 0.9 +force_to_hysteresis = 9e-10 +min_hys = 99 +max_hys = -99 + +coil_heat = 0 +coil_cooling = 0.9997 +coil_heat_mul = 3e-15 +max_heat = 0 + +displacement_mul = 1e-9 + +for c in range(input_wav.shape[1]): + print("loopi", c) + dpos = 0.0 + pos = 0.0 + for i in range(input_wav.shape[0]): + force = 0 + if (i >= 2): + force = (-0.01 * (input_wav[i-2][c] + input_wav[i][c]) + + 1.02 * input_wav[i-1][c]) + + v = force + for k in range(4): + dpos *= damping + dpos += 0.25 * force + pos += 0.25 * dpos; + v += 0.25 * suspension * pos + pos *= 0.99825 + + + #print (v) + coil_heat += abs(v * v) + coil_heat *= coil_cooling + + hysteresis += force_to_hysteresis * v + hysteresis *= hysteresis_damping + + min_hys = min(min_hys, hysteresis) + max_hys = max(max_hys, hysteresis) + #hysteresis = min(max(hysteresis, -0.005), 0.005) + + max_heat = max(max_heat, coil_heat) + output[i][c] = v + output[i][c] *= 1.0 - hysteresis + output[i][c] *= 1.0 + coil_heat * coil_heat_mul + #output[i][c] *= 1.0 + 1e-39 * abs(pos) ** 4 + + +print("max stats", min_hys, max_hys, max_heat * coil_heat_mul) + +output *= 0.3 / 32768. + +scipy.io.wavfile.write('/tmp/o.wav', samplerate, output) diff --git a/optimizer/simplex_fork b/optimizer/simplex_fork new file mode 100755 index 0000000..140f8cf --- /dev/null +++ b/optimizer/simplex_fork @@ -0,0 +1,226 @@ +#!/usr/bin/python3 + +# Copyright 2024 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Implementation of simplex search for an external process. + +The external process gets the input vector through environment variables. +Input of vector as setenv("VAR%dimension", val) +Getting the optimized function with regexp match from stdout +of the forked process. + +https://en.wikipedia.org/wiki/Nelder%E2%80%93Mead_method + +start as ./simplex_fork -n dimensions -s amount -- command +""" + +import argparse +import copy +import os +import random +import re +import subprocess +import sys + +def Midpoint(simplex): + """Nelder-Mead-like simplex midpoint calculation.""" + simplex.sort() + dim = len(simplex) - 1 + retval = [None] + [0.0] * dim + for i in range(1, dim + 1): + for k in range(dim): + retval[i] += simplex[k][i] + retval[i] /= dim + return retval + + +def Subtract(a, b): + """Vector arithmetic, with [0] being ignored.""" + return [None if k == 0 else a[k] - b[k] for k in range(len(a))] + +def Add(a, b): + """Vector arithmetic, with [0] being ignored.""" + return [None if k == 0 else a[k] + b[k] for k in range(len(a))] + +def Average(a, b): + """Vector arithmetic, with [0] being ignored.""" + return [None if k == 0 else 0.5 * (a[k] + b[k]) for k in range(len(a))] + + +eval_hash = {} + +def EvalCacheForget(): + global eval_hash + eval_hash = {} + +def Eval(vec, command, cached=True): + """Evaluates the objective function by forking a process. + + Args: + vec: [0] will be set to the objective function, [1:] will + contain the vector position for the objective function. + command: the command to run. + """ + global eval_hash + key = "" + # os.environ["BUTTERAUGLI_OPTIMIZE"] = "1" + for i in range(300): + os.environ["VAR%d" % i] = "0" + for i in range(len(vec) - 1): + os.environ["VAR%d" % i] = str(vec[i + 1]) + key += str(vec[i + 1]) + ":" + if cached and (key in eval_hash): + vec[0] = eval_hash[key] + return + + process = subprocess.Popen( + command, + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + env=dict(os.environ)) + + # process.wait() + vec[0] = 1e33 + for line in process.communicate(input=None)[0].splitlines(): + line = line.decode('ascii').strip() + print("BE", line) + sys.stdout.flush() + if line.startswith('score='): + vec[0] = float(line.split('=')[1]) + break + + print("eval: ", vec) + if (vec[0] <= 0.0): + vec[0] = 1e30 + eval_hash[key] = vec[0] + +def Reflect(simplex, command): + """Main iteration step of Nelder-Mead optimization. Modifies `simplex`.""" + simplex.sort() + last = simplex[-1] + mid = Midpoint(simplex) + diff = Subtract(mid, last) + mirrored = Add(mid, diff) + Eval(mirrored, command) + if mirrored[0] > simplex[-2][0]: + print("\nStill worst\n\n") + # Still the worst, shrink towards the best. + shrinking = Average(simplex[-1], simplex[0]) + Eval(shrinking, command) + print("\nshrinking...\n\n") + simplex[-1] = shrinking + return + if mirrored[0] < simplex[0][0]: + # new best + print("\nNew Best\n\n") + even_further = Add(mirrored, diff) + Eval(even_further, command) + if even_further[0] < mirrored[0]: + print("\nEven Further\n\n") + mirrored = even_further + simplex[-1] = mirrored + # try to extend + return + else: + # not a best, not a worst point + simplex[-1] = mirrored + + +def OneDimensionalSearch(simplex, shrink, index): + # last appended was better than the best so far, try to replace it + last_attempt = simplex[-1][:] + best = simplex[0] + if last_attempt[0] < best[0]: + # try expansion of the amount + diff = simplex[-1][index] - simplex[0][index] + simplex[-1][index] = simplex[0][index] + shrink * diff + Eval(simplex[-1], g_binary) + if simplex[-1][0] < last_attempt[0]: + # it got better + return True + elif last_attempt[0] >= 0: + diff = simplex[-1][index] - simplex[0][index] + simplex[-1][index] = simplex[0][index] - diff + Eval(simplex[-1], g_binary) + if simplex[-1][0] < last_attempt[0]: + # it got better + return True + simplex[-1] = last_attempt + return False + +def InitialSimplex(vec, dim, amount): + """Initialize the simplex at origin.""" + EvalCacheForget() + best = vec[:] + Eval(best, g_binary) + retval = [best] + comp_order = list(range(1, dim + 1)) + random.shuffle(comp_order) + + for i in range(dim): + index = comp_order[i] + best = retval[0][:] + best[index] += amount + Eval(best, g_binary) + retval.append(best) + do_shrink = True + while OneDimensionalSearch(retval, 2.0, index): + print("OneDimensionalSearch-Grow") + while OneDimensionalSearch(retval, 1.1, index): + print("OneDimensionalSearch-SlowGrow") + do_shrink = False + if do_shrink: + while OneDimensionalSearch(retval, 0.9, index): + print("OneDimensionalSearch-SlowShrinking") + retval.sort() + return retval + + +parser = argparse.ArgumentParser() +parser.add_argument('-n', '--num_dimensions', type=int, required=True) +parser.add_argument('-s', '--simplex_size', type=float, required=True) +parser.add_argument('command', nargs='+') +args = parser.parse_args() +g_dim = args.num_dimensions +g_amount = args.simplex_size +g_binary = args.command +g_simplex = InitialSimplex([None] + [0.0] * g_dim, + g_dim, 7.0 * g_amount) +best = g_simplex[0][:] +g_simplex = InitialSimplex(best, g_dim, g_amount * 2.47) +best = g_simplex[0][:] +g_simplex = InitialSimplex(best, g_dim, g_amount) +best = g_simplex[0][:] +g_simplex = InitialSimplex(best, g_dim, g_amount * 0.33) +best = g_simplex[0][:] + +bests = [] +try: + for restarts in range(99999): + for ii in range(g_dim * 5): + g_simplex.sort() + print("reflect", ii, g_simplex[0]) + Reflect(g_simplex, g_binary) + + mulli = 0.1 + 15 * random.random()**2.0 + print("\n\n\nRestart", restarts, "mulli", mulli) + g_simplex.sort() + best = g_simplex[0][:] + bests.append(best) + g_simplex = InitialSimplex(best, g_dim, g_amount * mulli) +except KeyboardInterrupt: + print("\nStopped.\n") + +print(f"{bests=}") diff --git a/speaker_experiments/angular.cc b/speaker_experiments/angular.cc new file mode 100644 index 0000000..24e80f8 --- /dev/null +++ b/speaker_experiments/angular.cc @@ -0,0 +1,219 @@ +// Copyright 2024 Google LLC +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// https://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include +#include +#include +#include +#include +#include + +#include "absl/flags/flag.h" +#include "absl/flags/parse.h" +#include "absl/log/check.h" +#include "fftw3.h" +#include "sndfile.hh" + +namespace { + +constexpr int kSubSourcePrecision = 10; + +struct FFTWDeleter { + void operator()(void* p) const { fftwf_free(p); } +}; +template +using FFTWUniquePtr = std::unique_ptr; + +float SquaredNorm(const fftwf_complex c) { return c[0] * c[0] + c[1] * c[1]; } + +float MicrophoneResponse(const float angle) { + return 0.5f * (2.5f + std::cos(angle)); +} + +float ExpectedLeftToRightRatio(const float angle) { + return (1e-3 + MicrophoneResponse(angle + M_PI / 4)) / + (1e-3 + MicrophoneResponse(angle - M_PI / 4)); +} + +float ActualLeftToRightRatio(const fftwf_complex left, + const fftwf_complex right) { + return std::sqrt((1e-3 + SquaredNorm(left)) / (1e-3 + SquaredNorm(right))); +} + +template +void Process( + const int window_size, const int overlap, const int output_channels, + const float distance_to_interval_ratio, In& input_stream, + Out& output_stream, const std::function& start_progress = [] {}, + const std::function& set_progress = [](int64_t written) {}) { + const int skip_size = window_size / overlap; + const float normalizer = 2.f / (window_size * overlap); + + FFTWUniquePtr input_fft( + fftwf_alloc_complex(2 * (window_size / 2 + 1))), + output_fft(fftwf_alloc_complex(output_channels * (window_size / 2 + 1))); + FFTWUniquePtr windowed_input(fftwf_alloc_real(2 * window_size)), + synthesized_output(fftwf_alloc_real(output_channels * window_size)); + std::vector input(2 * window_size), + output(output_channels * window_size); + + fftwf_plan left_right_fft = fftwf_plan_many_dft_r2c( + /*rank=*/1, /*n=*/&window_size, /*howmany=*/2, + /*in=*/windowed_input.get(), /*inembed=*/nullptr, /*istride=*/2, + /*idist=*/1, /*out=*/input_fft.get(), /*onembed=*/nullptr, /*ostride=*/2, + /*odist=*/1, /*flags=*/FFTW_PATIENT | FFTW_DESTROY_INPUT); + + fftwf_plan output_ifft = fftwf_plan_many_dft_c2r( + /*rank=*/1, /*n=*/&window_size, /*howmany=*/output_channels, + /*in=*/output_fft.get(), /*inembed=*/nullptr, /*istride=*/output_channels, + /*idist=*/1, /*out=*/synthesized_output.get(), /*onembed=*/nullptr, + /*ostride=*/output_channels, /*odist=*/1, + /*flags=*/FFTW_PATIENT | FFTW_DESTROY_INPUT); + + std::vector speaker_to_ratio_table; + speaker_to_ratio_table.reserve(kSubSourcePrecision * (output_channels - 1) + + 1); + for (int i = 0; i < kSubSourcePrecision * (output_channels - 1) + 1; ++i) { + const float x_div_interval = static_cast(i) / kSubSourcePrecision - + 0.5f * (output_channels - 1); + const float x_div_distance = x_div_interval / distance_to_interval_ratio; + const float angle = std::atan(x_div_distance); + speaker_to_ratio_table.push_back(ExpectedLeftToRightRatio(angle)); + } + + std::vector window_function; + window_function.reserve(window_size); + for (int i = 0; i < window_size; ++i) { + const float sine = std::sin(i * M_PI / (window_size - 1)); + window_function.push_back(sine * sine); + } + + start_progress(); + int64_t read = 0, written = 0, index = 0; + for (;;) { + read += input_stream.readf(input.data() + 2 * (window_size - skip_size), + skip_size); + + for (int i = 0; i < window_size; ++i) { + windowed_input[2 * i] = window_function[i] * input[2 * i]; + windowed_input[2 * i + 1] = window_function[i] * input[2 * i + 1]; + } + + fftwf_execute(left_right_fft); + + for (int i = 0; i < output_channels * (window_size / 2 + 1); ++i) { + std::fill(std::begin(output_fft[i]), std::end(output_fft[i]), 0.f); + } + + for (int i = 0; i < window_size / 2 + 1; ++i) { + const float ratio = + ActualLeftToRightRatio(input_fft[2 * i], input_fft[2 * i + 1]); + const int subspeaker_index = + std::lower_bound(speaker_to_ratio_table.begin(), + speaker_to_ratio_table.end(), ratio, + std::greater<>()) - + speaker_to_ratio_table.begin(); + const float index = + static_cast(subspeaker_index) / kSubSourcePrecision; + float integral_index_f; + const float fractional_index = std::modf(index, &integral_index_f); + const int integral_index = integral_index_f; + const fftwf_complex source_coefficient = { + 0.5f * (input_fft[2 * i][0] + input_fft[2 * i + 1][0]), + 0.5f * (input_fft[2 * i][1] + input_fft[2 * i + 1][1])}; + if (fractional_index < 1.f / (2 * kSubSourcePrecision)) { + std::copy_n(source_coefficient, 2, + output_fft[i * output_channels + integral_index]); + } else { + const float a = 1 - fractional_index; + const float b = fractional_index; + output_fft[i * output_channels + integral_index][0] = + a * source_coefficient[0]; + output_fft[i * output_channels + integral_index][1] = + a * source_coefficient[1]; + output_fft[i * output_channels + integral_index + 1][0] = + b * source_coefficient[0]; + output_fft[i * output_channels + integral_index + 1][1] = + b * source_coefficient[1]; + } + } + + fftwf_execute(output_ifft); + + for (int i = 0; i < output_channels * window_size; ++i) { + output[i] += synthesized_output[i]; + } + + if (index >= window_size - skip_size) { + for (int i = 0; i < output_channels * skip_size; ++i) { + output[i] *= normalizer; + } + const int64_t to_write = std::min(skip_size, read - written); + output_stream.writef(output.data(), to_write); + written += to_write; + set_progress(written); + if (written == read) break; + } + + std::copy(input.begin() + 2 * skip_size, input.begin() + 2 * window_size, + input.begin()); + std::fill_n(input.begin() + 2 * (window_size - skip_size), 2 * skip_size, + 0); + std::copy(output.begin() + output_channels * skip_size, output.end(), + output.begin()); + std::fill_n(output.begin() + output_channels * (window_size - skip_size), + output_channels * skip_size, 0); + + index += skip_size; + } + + fftwf_destroy_plan(left_right_fft); + fftwf_destroy_plan(output_ifft); +} + +} // namespace + +ABSL_FLAG(int, overlap, 64, "how much to overlap the FFTs"); +ABSL_FLAG(int, window_size, 4096, "FFT window size"); +ABSL_FLAG(int, output_channels, 12, "number of output channels"); +ABSL_FLAG(float, distance_to_interval_ratio, 4, + "ratio of (distance between microphone and source array) / (distance " + "between each source); default = 40cm / 10cm = 4"); + +int main(int argc, char** argv) { + absl::ParseCommandLine(argc, argv); + + const int window_size = absl::GetFlag(FLAGS_window_size); + const int overlap = absl::GetFlag(FLAGS_overlap); + const int output_channels = absl::GetFlag(FLAGS_output_channels); + const float distance_to_interval_ratio = + absl::GetFlag(FLAGS_distance_to_interval_ratio); + + QCHECK_EQ(window_size % overlap, 0); + + QCHECK_EQ(argc, 3) << "Usage: " << argv[0] << " "; + + SndfileHandle input_file(argv[1]); + QCHECK(input_file) << input_file.strError(); + + QCHECK_EQ(input_file.channels(), 2); + + SndfileHandle output_file( + argv[2], /*mode=*/SFM_WRITE, /*format=*/SF_FORMAT_WAV | SF_FORMAT_PCM_24, + /*channels=*/output_channels, /*samplerate=*/input_file.samplerate()); + + Process( + window_size, overlap, output_channels, distance_to_interval_ratio, + input_file, output_file, [] {}, [](const int64_t written) {}); +} diff --git a/speaker_experiments/audio_closed_loop b/speaker_experiments/audio_closed_loop new file mode 100755 index 0000000..58bc89a --- /dev/null +++ b/speaker_experiments/audio_closed_loop @@ -0,0 +1,157 @@ +#!/usr/bin/env python + +# Copyright 2024 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Usage: ./audio_closed_loop input.wav recorded.wav [ [ []]] +""" + +import argparse +import signal +import subprocess +import sys +import tempfile + +import numpy as np +import soundfile as sf + + +def detect_offset(samples: np.ndarray, sample_rate: int) -> int: + """Helps trim a recording that starts with a synchronization beep. + + Args: + samples (np.ndarray): The audio samples, of shape (num_samples,). + sample_rate (int): The sample rate in Hz. + + Returns: + How many samples to remove from the beginning to get exactly to the peak + of the synchronization sound. + """ + if samples.shape[0] < 0.01 * sample_rate: + raise ValueError + + kernel = (-2.) ** -np.abs(np.arange(-24, 24 + 1)) + samples = np.convolve(samples, kernel, mode='same') + + # Require the beep to be at least 10dB above the background noise in amplitude + min_ratio = 10**(10/20) + max_background = max(1e-7, np.max(np.abs(samples[:int(0.002 * sample_rate)]))) + max_above = None + last_above = None + for i in range(int(0.002 * sample_rate), samples.shape[0]): + if np.abs(samples[i]) >= min_ratio * max_background: + last_above = i + if max_above is None or np.abs(samples[i]) >= np.abs(samples[max_above]): + max_above = i + + if last_above is not None and last_above < i - int(0.002 * sample_rate): + return max_above + + raise ValueError + + +if __name__ == '__main__': + parser = argparse.ArgumentParser(prog='audio_closed_loop') + parser.add_argument('input', metavar='input.wav') + parser.add_argument('--write_recorded_to', metavar='recorded.wav') + parser.add_argument('--write_recorded_trimmed_to', metavar='recorded_trimmed.wav') + parser.add_argument('--norm', type=float, default=-28) + parser.add_argument('-b', '--beep_peak', type=float, default=-3) + parser.add_argument('-c', '--channel', type=int, default=5, help="in which output channel to place the audio") + parser.add_argument('-n', '--num_channels', type=int, default=20) + parser.add_argument('--num_recording_channels', type=int, default=18) + parser.add_argument('-m', '--microphone', type=int, default=1, help="channel of the microphone") + parser.add_argument('-f', '--flip', action=argparse.BooleanOptionalAction, default=True) + parser.add_argument('--driver_model', required=True) + parser.add_argument('--spectrum_similarity', required=True) + parser.add_argument('-p', '--playback_device', + default='hw:CARD=UMC1820,DEV=0') + parser.add_argument('-r', '--recording_device', + default='hw:CARD=UMC1820,DEV=0') + args = parser.parse_args() + + beep_peak_dBFS = args.beep_peak + beep_peak = 10**(beep_peak_dBFS / 20) + norm_dBFS = args.norm + norm = 10**(norm_dBFS / 20) + ramp_size = 24 + + recording_frequency = 48000 + + input_data, samplerate = sf.read(args.input) + if len(input_data.shape) > 1: + print(f"expected mono input, got {input_data.shape[1]} channels", file=sys.stderr) + sys.exit(1) + + if samplerate != recording_frequency: + print(f"expected {recording_frequency}Hz input, got {samplerate}Hz", file=sys.stderr) + sys.exit(1) + + input_data = np.pad(input_data, (int(0.01 * samplerate), 0)) + half_second = np.arange(samplerate // 2) + input_data[int(0.005 * samplerate) - ramp_size : int(0.005 * samplerate) + ramp_size + 1] = beep_peak * (-2.) ** -np.abs(np.arange(-ramp_size, ramp_size + 1)) + input_data *= norm + + prefixed_with_beep = tempfile.NamedTemporaryFile(suffix='.wav') + sf.write(prefixed_with_beep, input_data, samplerate, subtype='PCM_24') + + modeled_with_beep = tempfile.NamedTemporaryFile(suffix='.wav') + subprocess.run([args.driver_model, prefixed_with_beep.name, modeled_with_beep.name], check=True) + prefixed_with_beep.close() + + for_speakers = tempfile.NamedTemporaryFile(suffix='.wav') + remix = ['0'] * args.num_channels + remix[args.channel - 1] = '1' + subprocess.run(['sox', modeled_with_beep.name, for_speakers.name, 'remix', *remix, 'norm', str(args.norm)], check=True) + modeled_with_beep.close() + + if args.write_recorded_to is None: + recorded_with_beep = tempfile.NamedTemporaryFile(suffix='.wav') + write_recorded_to = recorded_with_beep.name + else: + write_recorded_to = args.write_recorded_to + record_process = subprocess.Popen(['arecord', f'-c{args.num_recording_channels}', '-f', 'S32_LE', f'-r{recording_frequency}', '-D', args.recording_device, write_recorded_to]) + + play = subprocess.run(['aplay', '-D', args.playback_device, for_speakers.name]) + if play.returncode != 0: + record_process.terminate() + sys.exit(play.returncode) + + record_process.send_signal(signal.SIGINT) + for_speakers.close() + record_process.wait() + + recorded_samples, recorded_samplerate = sf.read(write_recorded_to, always_2d=True) + if args.flip: + recorded_samples = -recorded_samples + + if args.write_recorded_trimmed_to is None: + recorded_trimmed = tempfile.NamedTemporaryFile(suffix='.wav') + write_recorded_trimmed_to = recorded_trimmed.name + else: + write_recorded_trimmed_to = args.write_recorded_trimmed_to + + try: + offset = detect_offset(recorded_samples[:, args.microphone - 1], recorded_samplerate) + print(f"Beep detected {offset / recorded_samplerate} seconds into the recording") + sf.write(write_recorded_trimmed_to, recorded_samples[offset + int(0.005 * recording_frequency):, args.microphone - 1], recorded_samplerate, subtype='PCM_24') + except ValueError: + print("No beep detected, writing the recorded audio as-is", file=sys.stderr) + if args.write_recorded_trimmed_to is not None: + sf.write(write_recorded_trimmed_to, recorded_samples, recorded_samplerate, subtype='PCM_24') + sys.exit(17) + + similarity = subprocess.run([args.spectrum_similarity, args.input, write_recorded_trimmed_to], check=True, capture_output=True) + + print(f"score={similarity.stdout.decode('ascii').strip()}") diff --git a/speaker_experiments/emphasizer.cc b/speaker_experiments/emphasizer.cc new file mode 100644 index 0000000..204e77a --- /dev/null +++ b/speaker_experiments/emphasizer.cc @@ -0,0 +1,352 @@ +// Copyright 2024 Google LLC +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// https://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include +#include +#include +#include +#include +#include +#include +#include // NOLINT +#include + +#include "absl/flags/flag.h" +#include "absl/flags/parse.h" +#include "absl/log/check.h" +#include "sndfile.hh" + +namespace { + +constexpr int kSubSourcePrecision = 1000; + +double MicrophoneResponse(const double angle) { + return 0.5f * (1.f + std::cos(angle)); +} + +double ExpectedLeftToRightRatio(const double angle) { + return (1e-3 + MicrophoneResponse(angle + M_PI / 4)) / + (1e-3 + MicrophoneResponse(angle - M_PI / 4)); +} + +double ActualLeftToRightRatio(const double squared_left, + const double squared_right) { + return std::sqrt((1e-13 + squared_left) / (1e-13 + squared_right)); +} + +double FindMedian3xLeaker(double window) { + // TODO(jyrki): This function needs more work. + // return -2.0/log(window); // Faster approximate function. + double half_way_to_total_sum = 1e300; + for (int k = 0; k < 2; ++k) { + double sum = 0; + double v0 = 1; + double v1 = 0; + double v2 = 0; + for (int i = 0; i < 65000; ++i) { + v1 += v0; + v2 += v1; + v0 *= window; + v1 *= window; + v2 *= window; + + double amp = v2; + sum += v2 * amp; + if (sum >= half_way_to_total_sum) { + return i; + } + } + half_way_to_total_sum = 0.48 * sum; // Sounds better when not quite half. + } + return 65000; +} + +double CalcReverbRatio(double frequency) { + if (frequency < 500) { + return 0; // no low frequency reverb + } + if (frequency < 1000) { + return (frequency - 500.0) / 500.0; // ramp up to full reverb at 1 kHz + } + if (frequency < 1500) { + return 1.0; // full + } + if (frequency < 2500) { + return 1.0 - 0.5 * fabs(frequency - 2000) / 500; // dip here for 'notch' + } + if (frequency < 4000) { + return 1.0; // full + } + if (frequency < 6000) { + return 0.1 + 0.9 * (6000 - frequency) / 2000; // slope down 4 kHz to 6 kHz + } + if (frequency < 10000) { + return 0.1 * (10000 - frequency) / 4000; // slope down 6 kHz to 10 kHz + } + return 0; +} + +struct Rotator { + std::complex rot[5] = {{1, 0}, 0}; + double window = 0.9999; // at 40 Hz. + double windowM1 = 1 - window; + double windowD = 0.99995; + double windowDM1 = 1 - windowD; + std::complex exp_mia; + int ix = 0; + double advance = 0; + double reverb_ratio = 0; + + Rotator(double frequency, const double sample_rate) { + window = pow(window, std::max(1.0, frequency / 40.0)); + windowD = pow(windowD, std::max(1.0, frequency / 2000.0)); + advance = 40000 - FindMedian3xLeaker(window); + if (advance < 1) { + advance = 1; + } + if (advance >= 0xfff0) { + advance = 0xfff0; + } + windowM1 = 1.0 - window; + windowDM1 = 1.0 - windowD; + frequency *= 2 * M_PI / sample_rate; + exp_mia = {std::cos(frequency), -std::sin(frequency)}; + reverb_ratio = CalcReverbRatio(frequency); + } + + void Increment(double audio) { + audio *= 0.01; + rot[0] *= exp_mia; + rot[1] *= window; + rot[2] *= window; + rot[3] *= window; + rot[4] *= windowD; + + rot[1] += windowM1 * audio * rot[0]; + rot[2] += windowM1 * rot[1]; + rot[3] += windowM1 * rot[2]; + rot[4] += windowDM1 * sqrt(std::norm(rot[3])); + ix++; + } + void GetSample(double* v) { + double excess = (1.0 * sqrt(std::norm(rot[4]))) - sqrt((std::norm(rot[3]))); + if (excess < 0) { + excess = 0; + } + float ratio_to_excess_init = + -excess / (sqrt(std::norm(rot[3])) + sqrt(std::norm(rot[4])) + 1e-8); + + float ratio_to_excess = exp(8 * ratio_to_excess_init); // most dry sound + float ratio_to_excess2 = + exp(2 * ratio_to_excess_init); // slightly less dry + if (ratio_to_excess < 0) { + ratio_to_excess = 0; + } + if (ratio_to_excess >= 1) { + ratio_to_excess = 1; + } + if (ratio_to_excess2 < 0) { + ratio_to_excess2 = 0; + } + if (ratio_to_excess2 >= 1) { + ratio_to_excess2 = 1; + } + double val = rot[0].real() * rot[3].real() + rot[0].imag() * rot[3].imag(); + + v[0] = ratio_to_excess * val; + v[1] = (ratio_to_excess2 - ratio_to_excess) * val; + v[2] = (1.0 - ratio_to_excess2) * val; + + // Bring some of reverbed sound from v[1] and v[2] back to non-reverbed + // v[0] depending on the reverb_ratio. + v[0] += (1.0 - reverb_ratio) * (v[1] + v[2]); + v[1] *= reverb_ratio; + v[2] *= reverb_ratio; + } + double SquaredAmplitude() const { return std::norm(rot[3]); } +}; + +double BarkFreq(double v) { + // should be larger for human hearing, around 0.165, but bass quality seems to + // suffer + constexpr double linlogsplit = 0.1; + if (v < linlogsplit) { + return 20.0 + (v / linlogsplit) * 20.0; // Linear 20-40 Hz. + } else { + float normalized_v = (v - linlogsplit) * (1.0 / (1.0 - linlogsplit)); + return 40.0 * pow(500.0, normalized_v); // Logarithmic 40-20000 Hz. + } +} + +static constexpr int64_t kBlockSize = 32768; +static const int kHistorySize = (1 << 18); +static const int kHistoryMask = kHistorySize - 1; + +class TaskExecutor { + public: + TaskExecutor(size_t num_threads, size_t output_channels) + : thread_outputs_(num_threads) { + output_channels_ = output_channels; + for (std::vector& output : thread_outputs_) { + output.resize(output_channels * kBlockSize, 0.f); + } + } + + void Execute(size_t num_tasks, size_t read, size_t total, + const double* history, Rotator* rot_left, Rotator* rot_right) { + read_ = read; + total_ = total; + history_ = history; + rot_left_ = rot_left; + rot_right_ = rot_right; + num_tasks_ = num_tasks; + next_task_ = 0; + std::vector> futures; + size_t num_threads = thread_outputs_.size(); + futures.reserve(num_threads); + for (size_t i = 0; i < num_threads; ++i) { + futures.push_back( + std::async(std::launch::async, &TaskExecutor::Run, this, i)); + } + for (size_t i = 0; i < num_threads; ++i) futures[i].get(); + } + + void Run(size_t thread) { + while (true) { + size_t my_task = next_task_++; + if (my_task >= num_tasks_) return; + std::vector& thread_output = thread_outputs_[thread]; + for (int i = 0; i < read_; ++i) { + int delayed_ix = total_ + i - rot_left_[my_task].advance; + float delayed_r = history_[2 * (delayed_ix & kHistoryMask) + 0]; + float delayed_g = history_[2 * (delayed_ix & kHistoryMask) + 1]; + + rot_left_[my_task].Increment(delayed_r); + rot_right_[my_task].Increment(delayed_g); + double left[3] = {0}; + double right[3] = {0}; + rot_left_[my_task].GetSample(&left[0]); + rot_right_[my_task].GetSample(&right[0]); + + thread_output[i * output_channels_ + 0] += left[0]; + thread_output[i * output_channels_ + 1] += right[0]; + thread_output[i * output_channels_ + 2] += left[1]; + thread_output[i * output_channels_ + 3] += right[1]; + thread_output[i * output_channels_ + 4] += left[2]; + thread_output[i * output_channels_ + 5] += right[2]; + } + } + } + + int64_t read_; + int64_t total_; + size_t num_tasks_; + size_t output_channels_; + Rotator* rot_left_; + Rotator* rot_right_; + const double* history_; + std::vector> thread_outputs_; + std::atomic next_task_{0}; +}; + +template +void Process( + const int output_channels, const double distance_to_interval_ratio, + In& input_stream, Out& output_stream, + const std::function& start_progress = [] {}, + const std::function& set_progress = [](int64_t written) {}) { + std::vector history(input_stream.channels() * kHistorySize); + std::vector input(input_stream.channels() * kBlockSize); + std::vector output(output_channels * kBlockSize); + + std::vector rot_left, rot_right; + constexpr int64_t kNumRotators = 512; + rot_left.reserve(kNumRotators); + rot_right.reserve(kNumRotators); + for (int i = 0; i < kNumRotators; ++i) { + const double frequency = + BarkFreq(static_cast(i) / (kNumRotators - 1)); + rot_left.emplace_back(frequency, input_stream.samplerate()); + rot_right.emplace_back(frequency, input_stream.samplerate()); + } + + std::vector speaker_to_ratio_table; + speaker_to_ratio_table.reserve(kSubSourcePrecision * (output_channels - 1) + + 1); + for (int i = 0; i < kSubSourcePrecision * (output_channels - 1) + 1; ++i) { + const double x_div_interval = static_cast(i) / kSubSourcePrecision - + 0.5f * (output_channels - 1); + const double x_div_distance = x_div_interval / distance_to_interval_ratio; + const double angle = std::atan(x_div_distance); + speaker_to_ratio_table.push_back(ExpectedLeftToRightRatio(angle)); + } + + TaskExecutor pool(40, output_channels); + + start_progress(); + int64_t total = 0; + for (;;) { + const int64_t read = input_stream.readf(input.data(), kBlockSize); + for (int i = 0; i < read; ++i) { + int input_ix = i + total; + history[2 * (input_ix & kHistoryMask) + 0] = input[2 * i]; + history[2 * (input_ix & kHistoryMask) + 1] = input[2 * i + 1]; + } + if (read == 0) break; + + pool.Execute(kNumRotators, read, total, history.data(), rot_left.data(), + rot_right.data()); + + std::fill(output.begin(), output.end(), 0); + for (std::vector& thread_output : pool.thread_outputs_) { + for (int i = 0; i < output.size(); ++i) { + output[i] += thread_output[i]; + thread_output[i] = 0.f; + } + } + output_stream.writef(output.data(), read); + total += read; + set_progress(total); + } +} + +} // namespace + +ABSL_FLAG(int, output_channels, 6, "number of output channels"); +ABSL_FLAG(double, distance_to_interval_ratio, 4, + "ratio of (distance between microphone and source array) / (distance " + "between each source); default = 40cm / 10cm = 4"); + +int main(int argc, char** argv) { + absl::ParseCommandLine(argc, argv); + + const int output_channels = absl::GetFlag(FLAGS_output_channels); + const double distance_to_interval_ratio = + absl::GetFlag(FLAGS_distance_to_interval_ratio); + + QCHECK_EQ(argc, 3) << "Usage: " << argv[0] << " "; + + SndfileHandle input_file(argv[1]); + QCHECK(input_file) << input_file.strError(); + + QCHECK_EQ(input_file.channels(), 2); + + SndfileHandle output_file( + argv[2], /*mode=*/SFM_WRITE, /*format=*/SF_FORMAT_WAV | SF_FORMAT_PCM_24, + /*channels=*/output_channels, /*samplerate=*/input_file.samplerate()); + + Process( + output_channels, distance_to_interval_ratio, input_file, output_file, + [] {}, [](const int64_t written) {}); +} diff --git a/speaker_experiments/revolve.cc b/speaker_experiments/revolve.cc new file mode 100644 index 0000000..63156d2 --- /dev/null +++ b/speaker_experiments/revolve.cc @@ -0,0 +1,300 @@ +// Copyright 2024 Google LLC +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// https://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include +#include +#include +#include +#include +#include +#include // NOLINT +#include +#include + +#include "absl/flags/flag.h" +#include "absl/flags/parse.h" +#include "absl/log/check.h" + +namespace { + +constexpr int kSubSourcePrecision = 1000; + +double MicrophoneResponse(const double angle) { + return 0.5f * (1.f + std::cos(angle)); +} + +double ExpectedLeftToRightRatio(const double angle) { + return (1e-3 + MicrophoneResponse(angle + M_PI / 4)) / + (1e-3 + MicrophoneResponse(angle - M_PI / 4)); +} + +double ActualLeftToRightRatio(const double squared_left, + const double squared_right) { + return std::sqrt((1e-13 + squared_left) / (1e-13 + squared_right)); +} + +double FindMedian3xLeaker(double window) { + // return -2.58/log(window); // Faster approximate function. + double half_way_to_total_sum = 1e300; + for (int k = 0; k < 2; ++k) { + double sum = 0; + double v0 = 1; + double v1 = 0; + double v2 = 0; + double prev_v2 = 0; + for (int i = 0; i < 65000; ++i) { + v1 += v0; + v2 += v1; + v0 *= window; + v1 *= window; + v2 *= window; + sum += v2; + prev_v2 = v2; + if (sum >= half_way_to_total_sum) { + return i; + } + } + half_way_to_total_sum = 0.45 * sum; // Sounds better when not quite half. + } + return 65000; +} + +struct Rotator { + std::complex rot[4] = {{1, 0}, 0}; + double window = 0.99963; // at 200 Hz. + double windowM1 = 1 - window; + std::complex exp_mia; + int ix = 0; + double advance = 0; + + Rotator(double frequency, const double sample_rate) { + window = pow(window, std::max(1.0, frequency / 200.0)); + advance = 40000 - FindMedian3xLeaker(window); + if (advance < 1) { + advance = 1; + } + if (advance >= 0xfff0) { + advance = 0xfff0; + } + windowM1 = 1.0 - window; + windowM1 = windowM1 * windowM1 * windowM1; + frequency *= 2 * M_PI / sample_rate; + exp_mia = {std::cos(frequency), -std::sin(frequency)}; + } + + void Increment(double audio) { + rot[0] *= exp_mia; + rot[1] *= window; + rot[2] *= window; + rot[3] *= window; + + rot[1] += audio * rot[0]; + rot[2] += rot[1]; + rot[3] += windowM1 * rot[2]; + ix++; + } + double GetSample() const { + return rot[0].real() * rot[3].real() + rot[0].imag() * rot[3].imag(); + } + + double SquaredAmplitude() const { return std::norm(rot[3]); } +}; + +double BarkFreq(double v) { + constexpr double linlogsplit = 0.165; + if (v < linlogsplit) { + return 20.0 + (v / linlogsplit) * 180.0; // Linear 20-200 Hz. + } else { + float normalized_v = (v - linlogsplit) * (1.0 / (1.0 - linlogsplit)); + return 200.0 * pow(100.0, normalized_v); // Logarithmic 200-20000 Hz. + } +} + +static constexpr int64_t kBlockSize = 16384; +static const int kHistorySize = (1 << 17); +static const int kHistoryMask = kHistorySize - 1; + +class TaskExecutor { + public: + TaskExecutor(size_t num_threads, size_t output_channels) + : thread_outputs_(num_threads) { + output_channels_ = output_channels; + for (std::vector& output : thread_outputs_) { + output.resize(output_channels * kBlockSize, 0.f); + } + } + + void Execute(size_t num_tasks, size_t read, size_t total, + const double* history, Rotator* rot_left, Rotator* rot_right) { + read_ = read; + total_ = total; + history_ = history; + rot_left_ = rot_left; + rot_right_ = rot_right; + num_tasks_ = num_tasks; + next_task_ = 0; + std::vector> futures; + size_t num_threads = thread_outputs_.size(); + futures.reserve(num_threads); + for (size_t i = 0; i < num_threads; ++i) { + futures.push_back( + std::async(std::launch::async, &TaskExecutor::Run, this, i)); + } + for (size_t i = 0; i < num_threads; ++i) futures[i].get(); + } + + void Run(size_t thread) { + while (true) { + size_t my_task = next_task_++; + if (my_task >= num_tasks_) return; + std::vector& thread_output = thread_outputs_[thread]; + for (int i = 0; i < read_; ++i) { + int delayed_ix = total_ + i - rot_left_[my_task].advance; + float delayed_r = history_[2 * (delayed_ix & kHistoryMask) + 0]; + float delayed_g = history_[2 * (delayed_ix & kHistoryMask) + 1]; + + rot_left_[my_task].Increment(delayed_r); + rot_right_[my_task].Increment(delayed_g); + + double left = rot_left_[my_task].SquaredAmplitude(), + right = rot_right_[my_task].SquaredAmplitude(); + + left = sqrt(left); + right = sqrt(right); + double index = 0.5 * ((output_channels_ - 1) + + 1.0 * (output_channels_ - 1) * (left - right) / + (left + right + 1e-10)); + + if (index < 0) { + index = 0; + } + if (index >= output_channels_) { + index = output_channels_ - 1; + } + double integral_index_f; + const double fractional_index = std::modf(index, &integral_index_f); + const int integral_index = integral_index_f; + const double sample = .5f * (rot_left_[my_task].GetSample() + + rot_right_[my_task].GetSample()); + thread_output[i * output_channels_ + integral_index] += + (1 - fractional_index) * sample; + if (integral_index < output_channels_) { + thread_output[i * output_channels_ + integral_index + 1] += + fractional_index * sample; + } + } + } + } + + int64_t read_; + int64_t total_; + size_t num_tasks_; + size_t output_channels_; + Rotator* rot_left_; + Rotator* rot_right_; + const double* history_; + std::vector> thread_outputs_; + std::atomic next_task_{0}; +}; + +template +void Process( + const int output_channels, const double distance_to_interval_ratio, + In& input_stream, Out& output_stream, + const std::function& start_progress = [] {}, + const std::function& set_progress = [](int64_t written) {}) { + std::vector history(input_stream.channels() * kHistorySize); + std::vector input(input_stream.channels() * kBlockSize); + std::vector output(output_channels * kBlockSize); + + std::vector rot_left, rot_right; + constexpr int64_t kNumRotators = 256; + rot_left.reserve(kNumRotators); + rot_right.reserve(kNumRotators); + for (int i = 0; i < kNumRotators; ++i) { + const double frequency = + BarkFreq(static_cast(i) / (kNumRotators - 1)); + rot_left.emplace_back(frequency, input_stream.samplerate()); + rot_right.emplace_back(frequency, input_stream.samplerate()); + } + + std::vector speaker_to_ratio_table; + speaker_to_ratio_table.reserve(kSubSourcePrecision * (output_channels - 1) + + 1); + for (int i = 0; i < kSubSourcePrecision * (output_channels - 1) + 1; ++i) { + const double x_div_interval = static_cast(i) / kSubSourcePrecision - + 0.5f * (output_channels - 1); + const double x_div_distance = x_div_interval / distance_to_interval_ratio; + const double angle = std::atan(x_div_distance); + speaker_to_ratio_table.push_back(ExpectedLeftToRightRatio(angle)); + } + + TaskExecutor pool(40, output_channels); + + start_progress(); + int64_t total = 0; + for (;;) { + const int64_t read = input_stream.readf(input.data(), kBlockSize); + for (int i = 0; i < read; ++i) { + int input_ix = i + total; + history[2 * (input_ix & kHistoryMask) + 0] = input[2 * i]; + history[2 * (input_ix & kHistoryMask) + 1] = input[2 * i + 1]; + } + if (read == 0) break; + + pool.Execute(kNumRotators, read, total, history.data(), rot_left.data(), + rot_right.data()); + + std::fill(output.begin(), output.end(), 0); + for (std::vector& thread_output : pool.thread_outputs_) { + for (int i = 0; i < output.size(); ++i) { + output[i] += thread_output[i]; + thread_output[i] = 0.f; + } + } + output_stream.writef(output.data(), read); + total += read; + set_progress(total); + } +} + +} // namespace + +ABSL_FLAG(int, output_channels, 12, "number of output channels"); +ABSL_FLAG(double, distance_to_interval_ratio, 4, + "ratio of (distance between microphone and source array) / (distance " + "between each source); default = 40cm / 10cm = 4"); + +int main(int argc, char** argv) { + absl::ParseCommandLine(argc, argv); + + const int output_channels = absl::GetFlag(FLAGS_output_channels); + const double distance_to_interval_ratio = + absl::GetFlag(FLAGS_distance_to_interval_ratio); + + QCHECK_EQ(argc, 3) << "Usage: " << argv[0] << " "; + + SndfileHandle input_file(argv[1]); + QCHECK(input_file) << input_file.strError(); + + QCHECK_EQ(input_file.channels(), 2); + + SndfileHandle output_file( + argv[2], /*mode=*/SFM_WRITE, /*format=*/SF_FORMAT_WAV | SF_FORMAT_PCM_24, + /*channels=*/output_channels, /*samplerate=*/input_file.samplerate()); + + Process( + output_channels, distance_to_interval_ratio, input_file, output_file, + [] {}, [](const int64_t written) {}); +} diff --git a/speaker_experiments/spectrum_similarity.cc b/speaker_experiments/spectrum_similarity.cc new file mode 100644 index 0000000..f452c8d --- /dev/null +++ b/speaker_experiments/spectrum_similarity.cc @@ -0,0 +1,251 @@ +// Copyright 2024 Google LLC +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// https://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include +#include +#include +#include +#include +#include +#include + +#include "absl/flags/flag.h" +#include "absl/flags/parse.h" +#include "absl/log/check.h" +#include "fftw3.h" +#include "sndfile.hh" + +ABSL_FLAG(bool, autoscale, true, + "whether to automatically scale the inputs so that the residuals " + "have equal power"); +ABSL_FLAG(int, overlap, 128, "how much to overlap the FFTs"); +ABSL_FLAG(int, window_size, 4096, "FFT window size"); + +namespace { + +struct FFTWDeleter { + void operator()(void* p) const { fftwf_free(p); } +}; +template +using FFTWUniquePtr = std::unique_ptr; + +float SquaredNorm(const fftwf_complex c) { return c[0] * c[0] + c[1] * c[1]; } + +float Similarity( + const int window_size, const int overlap, SndfileHandle& reference_input, + SndfileHandle& candidate_input, const float candidate_scaling, + float* reference_minus_candidate_residuals = nullptr, + const std::function& start_progress = [] {}, + const std::function& set_progress = [](int64_t) {}) { + reference_input.seek(0, SEEK_SET); + candidate_input.seek(0, SEEK_SET); + + const int skip_size = window_size / overlap; + const float normalizer = 2.f / (window_size * overlap); + + FFTWUniquePtr input_fft( + fftwf_alloc_complex(2 * (window_size / 2 + 1))), + center_fft(fftwf_alloc_complex(window_size / 2 + 1)); + FFTWUniquePtr windowed_input(fftwf_alloc_real(2 * window_size)), + center(fftwf_alloc_real(window_size)); + std::vector input(2 * window_size, 0); + std::vector output(3 * window_size); + std::vector window; + + window.reserve(window_size); + for (int i = 0; i < window_size; ++i) { + window.push_back(std::sin((i + .5f) * (M_PI / window_size))); + window.back() *= window.back(); + } + + fftwf_plan left_right_fft = fftwf_plan_many_dft_r2c( + /*rank=*/1, /*n=*/&window_size, /*howmany=*/2, + /*in=*/windowed_input.get(), /*inembed=*/nullptr, /*istride=*/1, + /*idist=*/window_size, /*out=*/input_fft.get(), /*onembed=*/nullptr, + /*ostride=*/2, /*odist=*/1, /*flags=*/FFTW_PATIENT | FFTW_DESTROY_INPUT); + + fftwf_plan center_ifft = fftwf_plan_dft_c2r_1d( + /*n0=*/window_size, /*in=*/center_fft.get(), /*out=*/center.get(), + /*flags=*/FFTW_MEASURE | FFTW_DESTROY_INPUT); + + float center_power = 0.f, total_power = 0.f; + if (reference_minus_candidate_residuals != nullptr) { + *reference_minus_candidate_residuals = 0.f; + } + + start_progress(); + int64_t read = 0, analyzed = 0, index = 0; + for (;;) { + read += + std::min(reference_input.readf(input.data() + window_size - skip_size, + skip_size), + candidate_input.readf( + input.data() + 2 * window_size - skip_size, skip_size)); + for (int i = 0; i < skip_size; ++i) { + input[2 * window_size - skip_size + i] *= candidate_scaling; + output[3 * (window_size - skip_size + i)] = + input[window_size - skip_size + i]; + output[3 * (window_size - skip_size + i) + 1] = + input[2 * window_size - skip_size + i]; + output[3 * (window_size - skip_size + i) + 2] = 0; + } + + for (int c = 0; c < 2; ++c) { + for (int i = 0; i < window_size; ++i) { + windowed_input[c * window_size + i] = + window[i] * input[c * window_size + i]; + } + } + + fftwf_execute(left_right_fft); + + for (int i = 0; i < window_size / 2 + 1; ++i) { + if (SquaredNorm(input_fft[i * 2]) < SquaredNorm(input_fft[i * 2 + 1])) { + std::copy_n(input_fft[i * 2], 2, center_fft[i]); + } else { + std::copy_n(input_fft[i * 2 + 1], 2, center_fft[i]); + } + } + + fftwf_execute(center_ifft); + + for (int i = 0; i < window_size; ++i) { + output[3 * i + 2] += center[i]; + } + + if (index >= window_size - skip_size) { + for (int i = 0; i < skip_size; ++i) { + output[3 * i + 2] *= normalizer; + output[3 * i] -= output[3 * i + 2]; + output[3 * i + 1] -= output[3 * i + 2]; + } + const int64_t to_analyze = std::min(skip_size, read - analyzed); + for (int64_t i = 0; i < to_analyze; ++i) { + const float center_squared = output[3 * i + 2] * output[3 * i + 2]; + const float left_squared = output[3 * i] * output[3 * i]; + const float right_squared = output[3 * i + 1] * output[3 * i + 1]; + center_power += center_squared; + total_power += center_squared + left_squared + right_squared; + if (reference_minus_candidate_residuals != nullptr) { + *reference_minus_candidate_residuals += left_squared - right_squared; + } + } + analyzed += to_analyze; + set_progress(analyzed); + if (analyzed == read) break; + } + + std::copy(input.begin() + skip_size, input.begin() + window_size, + input.begin()); + std::fill_n(input.begin() + window_size - skip_size, skip_size, 0); + std::copy(input.begin() + window_size + skip_size, + input.begin() + 2 * window_size, input.begin() + window_size); + std::fill_n(input.begin() + 2 * window_size - skip_size, skip_size, 0); + std::copy(output.begin() + 3 * skip_size, output.end(), output.begin()); + std::fill_n(output.begin() + 3 * (window_size - skip_size), 3 * skip_size, + 0); + + index += skip_size; + } + + fftwf_destroy_plan(left_right_fft); + fftwf_destroy_plan(center_ifft); + + return -10 * std::log10(center_power / total_power); +} + +float FindScaling(const int window_size, const int overlap, + SndfileHandle& reference_input, + SndfileHandle& candidate_input) { + // Scalings are in log2 scale until the very end. + + float min = 0.f, max = 0.f; + + float scaling = 0.f; + float difference; + Similarity(window_size, overlap, reference_input, candidate_input, + std::exp2(scaling), &difference); + const bool initial_sign = std::signbit(difference); + + bool have_both_bounds = false; + do { + if (initial_sign) { + // reference - scaling * candidate is negative, so scaling too high + scaling -= 1.f; + } else { + scaling += 1.f; + } + + Similarity(window_size, overlap, reference_input, candidate_input, + std::exp2(scaling), &difference); + if (std::signbit(difference) != initial_sign) { + have_both_bounds = true; + + if (initial_sign) { + min = scaling; + max = scaling + 1.f; + } else { + min = scaling - 1.f; + max = scaling; + } + } + } while (!have_both_bounds); + + while ((max - min) > 1e-2) { + scaling = .5f * (max + min); + Similarity(window_size, overlap, reference_input, candidate_input, + std::exp2(scaling), &difference); + if (std::signbit(difference)) { + max = scaling; + } else { + min = scaling; + } + } + + return std::exp2(.5f * (max + min)); +} + +} // namespace + +int main(int argc, char** argv) { + absl::ParseCommandLine(argc, argv); + + const int window_size = absl::GetFlag(FLAGS_window_size); + const int overlap = absl::GetFlag(FLAGS_overlap); + + QCHECK_EQ(window_size % overlap, 0); + + QCHECK_EQ(argc, 3) << "Usage: " << argv[0] << " "; + + SndfileHandle reference_input_file(argv[1]); + QCHECK(reference_input_file) << reference_input_file.strError(); + SndfileHandle candidate_input_file(argv[2]); + QCHECK(candidate_input_file) << candidate_input_file.strError(); + QCHECK_EQ(reference_input_file.channels(), 1); + QCHECK_EQ(candidate_input_file.channels(), 1); + QCHECK_EQ(reference_input_file.samplerate(), + candidate_input_file.samplerate()); + + const float scaling = + absl::GetFlag(FLAGS_autoscale) + ? FindScaling(window_size, /*overlap=*/8, reference_input_file, + candidate_input_file) + : 1.f; + + const float similarity = Similarity( + window_size, overlap, reference_input_file, candidate_input_file, scaling, + nullptr, [] {}, [](const int64_t written) {}); + + printf("%.17f\n", similarity); +} diff --git a/speaker_experiments/two_to_three.cc b/speaker_experiments/two_to_three.cc new file mode 100644 index 0000000..519932a --- /dev/null +++ b/speaker_experiments/two_to_three.cc @@ -0,0 +1,144 @@ +// Copyright 2024 Google LLC +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// https://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include +#include +#include +#include + +#include "absl/flags/flag.h" +#include "absl/flags/parse.h" +#include "absl/log/check.h" +#include "fftw3.h" +#include "sndfile.hh" + +ABSL_FLAG(int, overlap, 128, "how much to overlap the FFTs"); +ABSL_FLAG(int, window_size, 4096, "FFT window size"); + +namespace { + +struct FFTWDeleter { + void operator()(void* p) const { fftwf_free(p); } +}; +template +using FFTWUniquePtr = std::unique_ptr; + +float SquaredNorm(const fftwf_complex c) { return c[0] * c[0] + c[1] * c[1]; } + +template +void Process(const int window_size, const int overlap, In& input_stream, + Out& output_stream, const std::function& start_progress, + const std::function& set_progress) { + const int skip_size = window_size / overlap; + const float normalizer = 1.f / (window_size * overlap); + + FFTWUniquePtr input_fft( + fftwf_alloc_complex(2 * (window_size / 2 + 1))), + center_fft(fftwf_alloc_complex(window_size / 2 + 1)); + FFTWUniquePtr input(fftwf_alloc_real(2 * window_size)), + center(fftwf_alloc_real(window_size)); + std::fill_n(input.get(), 2 * window_size, 0); + std::vector output(3 * window_size); + + fftwf_plan left_right_fft = fftwf_plan_many_dft_r2c( + /*rank=*/1, /*n=*/&window_size, /*howmany=*/2, /*in=*/input.get(), + /*inembed=*/nullptr, /*istride=*/2, /*idist=*/1, /*out=*/input_fft.get(), + /*onembed=*/nullptr, /*ostride=*/2, /*odist=*/1, + /*flags=*/FFTW_PATIENT | FFTW_PRESERVE_INPUT); + + fftwf_plan center_ifft = fftwf_plan_dft_c2r_1d( + /*n0=*/window_size, /*in=*/center_fft.get(), /*out=*/center.get(), + /*flags=*/FFTW_MEASURE | FFTW_DESTROY_INPUT); + + start_progress(); + int64_t read = 0, written = 0, index = 0; + for (;;) { + read += input_stream.readf(input.get() + 2 * (window_size - skip_size), + skip_size); + for (int i = 0; i < skip_size; ++i) { + output[3 * (window_size - skip_size + i)] = + input[2 * (window_size - skip_size + i)]; + output[3 * (window_size - skip_size + i) + 1] = + input[2 * (window_size - skip_size + i) + 1]; + output[3 * (window_size - skip_size + i) + 2] = 0; + } + + fftwf_execute(left_right_fft); + + for (int i = 0; i < window_size / 2 + 1; ++i) { + if (SquaredNorm(input_fft[i * 2]) < SquaredNorm(input_fft[i * 2 + 1])) { + std::copy_n(input_fft[i * 2], 2, center_fft[i]); + } else { + std::copy_n(input_fft[i * 2 + 1], 2, center_fft[i]); + } + } + + fftwf_execute(center_ifft); + + for (int i = 0; i < window_size; ++i) { + output[3 * i + 2] += center[i]; + } + + if (index >= window_size - skip_size) { + for (int i = 0; i < skip_size; ++i) { + output[3 * i + 2] *= normalizer; + output[3 * i] -= output[3 * i + 2]; + output[3 * i + 1] -= output[3 * i + 2]; + } + const int64_t to_write = std::min(skip_size, read - written); + output_stream.writef(output.data(), to_write); + written += to_write; + set_progress(written); + if (written == read) break; + } + + std::copy(input.get() + 2 * skip_size, input.get() + 2 * window_size, + input.get()); + std::fill_n(input.get() + 2 * (window_size - skip_size), 2 * skip_size, 0); + std::copy(output.begin() + 3 * skip_size, output.end(), output.begin()); + std::fill_n(output.begin() + 3 * (window_size - skip_size), 3 * skip_size, + 0); + + index += skip_size; + } + + fftwf_destroy_plan(left_right_fft); + fftwf_destroy_plan(center_ifft); +} + +} // namespace + +int main(int argc, char** argv) { + absl::ParseCommandLine(argc, argv); + + const int window_size = absl::GetFlag(FLAGS_window_size); + const int overlap = absl::GetFlag(FLAGS_overlap); + + QCHECK_EQ(window_size % overlap, 0); + + QCHECK_EQ(argc, 3) << "Usage: " << argv[0] << " "; + + SndfileHandle input_file(argv[1]); + QCHECK(input_file) << input_file.strError(); + + QCHECK_EQ(input_file.channels(), 2); + + SndfileHandle output_file( + argv[2], /*mode=*/SFM_WRITE, /*format=*/SF_FORMAT_WAV | SF_FORMAT_PCM_24, + /*channels=*/3, /*samplerate=*/input_file.samplerate()); + + Process( + window_size, overlap, input_file, output_file, [] {}, + [](const int64_t written) {}); +} diff --git a/speaker_experiments/virtual_speakers.cc b/speaker_experiments/virtual_speakers.cc new file mode 100644 index 0000000..cf61357 --- /dev/null +++ b/speaker_experiments/virtual_speakers.cc @@ -0,0 +1,160 @@ +// Copyright 2024 Google LLC +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// https://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include +#include +#include +#include +#include +#include +#include + +#include "Eigen/Core" +#include "absl/algorithm/container.h" +#include "absl/flags/flag.h" +#include "absl/flags/parse.h" +#include "absl/log/check.h" +#include "absl/strings/numbers.h" +#include "absl/strings/str_split.h" +#include "absl/strings/string_view.h" +#include "sndfile.hh" + +ABSL_FLAG(std::string, input_file, "", + "Path to an audio file to be played back on the virtual speakers"); +ABSL_FLAG(std::string, output_file, "", "Where to write the output to"); +ABSL_FLAG( + std::string, virtual_speaker_positions, "-0.5,0.5;0.5,0.5", + "List of positions for the virtual speakers, where the middle of the array " + "is assumed to be at (0, 0), positive y is in front (towards the " + "listener), and positive x goes to the right when facing the array"); +ABSL_FLAG(float, speaker_separation, 0.1, + "Distance between each physical speaker of the array"); +ABSL_FLAG(int, num_speakers, 12, "Number of physical speakers in the array"); +ABSL_FLAG(float, speed_of_sound, 343.f, + "Speed of sound in distance units per second"); + +namespace { + +constexpr int64_t kBufferSize = 4096; + +} // namespace + +int main(int argc, char** argv) { + absl::ParseCommandLine(argc, argv); + + const std::string input_file = absl::GetFlag(FLAGS_input_file); + QCHECK(!input_file.empty()); + + const std::string output_file = absl::GetFlag(FLAGS_output_file); + QCHECK(!output_file.empty()); + + const int num_speakers = absl::GetFlag(FLAGS_num_speakers); + const float speed_of_sound = absl::GetFlag(FLAGS_speed_of_sound); + + SndfileHandle sound_file(input_file); + QCHECK(sound_file) << sound_file.strError(); + + const float speaker_separation = absl::GetFlag(FLAGS_speaker_separation); + const auto SpeakerPosition = [num_speakers, speaker_separation](const int i) { + return std::make_pair((num_speakers - 1.f) * speaker_separation * + (i / (num_speakers - 1.f) - .5f), + 0.f); + }; + + std::vector> virtual_speaker_positions; + for (absl::string_view microphone : + absl::StrSplit(absl::GetFlag(FLAGS_virtual_speaker_positions), ';')) { + const std::vector coordinates = + absl::StrSplit(microphone, ','); + QCHECK_EQ(coordinates.size(), 2); + float x, y; + QCHECK(absl::SimpleAtof(coordinates[0], &x)); + QCHECK(absl::SimpleAtof(coordinates[1], &y)); + virtual_speaker_positions.emplace_back(x, y); + } + + QCHECK_EQ(sound_file.channels(), virtual_speaker_positions.size()); + + const float samples_per_distance = sound_file.samplerate() / speed_of_sound; + + Eigen::ArrayXXi delays(num_speakers, virtual_speaker_positions.size()); + Eigen::ArrayXXf multipliers(num_speakers, virtual_speaker_positions.size()); + for (int c = 0; c < num_speakers; ++c) { + const auto [x, y] = SpeakerPosition(c); + for (int s = 0; s < virtual_speaker_positions.size(); ++s) { + const auto [vx, vy] = virtual_speaker_positions[s]; + const float dx = x - vx; + const float dy = y - vy; + const float distance = std::hypot(dx, dy); + if (vy <= y) { + // Behind + const float cos_angle = dy / distance; + delays(c, s) = std::lround(samples_per_distance * distance); + multipliers(c, s) = cos_angle / distance; + } else { + // In front + const float cos_angle = dy / distance; + delays(c, s) = std::lround(-samples_per_distance * distance); + // This happens to be equivalent to just `dy` but expressing it like + // this is perhaps clearer and makes it potentially easier to experiment + // with other possibilities. + // TODO(sboukortt): Notably, would cos_angle^2 possibly be better? Let's + // investigate this. + multipliers(c, s) = distance * cos_angle; + } + } + } + + // Prevent clipping. + multipliers /= multipliers.maxCoeff(); + + // Prevent having to start in the past. + delays -= delays.minCoeff(); + + std::vector input_samples(sound_file.channels() * sound_file.frames()); + QCHECK_EQ(sound_file.read(input_samples.data(), input_samples.size()), + input_samples.size()); + + const int64_t num_output_frames = sound_file.frames() + delays.maxCoeff(); + + SndfileHandle output_sound_file(output_file, /*mode=*/SFM_WRITE, + /*format=*/SF_FORMAT_WAV | SF_FORMAT_PCM_24, + /*channels=*/num_speakers, + /*samplerate=*/sound_file.samplerate()); + QCHECK(output_sound_file) << output_sound_file.strError(); + std::vector output_buffer(kBufferSize * output_sound_file.channels()); + for (int64_t i = 0; i < num_output_frames; i += kBufferSize) { + absl::c_fill(output_buffer, 0.f); + const int64_t buffer_size = std::min(kBufferSize, num_output_frames - i); + for (int c = 0; c < output_sound_file.channels(); ++c) { + // TODO: Gaussian or something like that + const float window = + (c == 0 || c == output_sound_file.channels() - 1) ? 0.5f : 1.f; + for (int s = 0; s < virtual_speaker_positions.size(); ++s) { + const int64_t delay = delays(c, s); + const float multiplier = window * multipliers(c, s); + const int64_t upper_bound = + std::min(buffer_size, sound_file.frames() + delay - i); + for (int64_t j = std::max(0, delay - i); j < upper_bound; + ++j) { + const int64_t source_i = i + j - delay; + output_buffer[j * output_sound_file.channels() + c] += + input_samples[source_i * sound_file.channels() + s] * multiplier; + } + } + } + + output_sound_file.writef(output_buffer.data(), buffer_size); + } +} diff --git a/testdata/a.wav b/testdata/a.wav new file mode 100644 index 0000000000000000000000000000000000000000..b694ab0d095c339f575816ea95c78a3d93f95b65 GIT binary patch literal 39246 zcmeFZ^_x{?*!R6^$8--}(jh6WfD+Oj0!j!7C?TMTh%{0P0#cG9CEX#7bf-jR 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