From c18dee85de6d3bf636dee94ff39c365f6a98ad94 Mon Sep 17 00:00:00 2001 From: Theo Walker Date: Tue, 26 Sep 2017 16:56:57 -0400 Subject: [PATCH] Add theo's data and contribution scripts --- README.md | 20 ++--- acquire_data/say_numbers_prompt.py | 67 +++++++++++++++ acquire_data/split_and_label_numbers.py | 104 ++++++++++++++++++++++++ metadata.py | 5 ++ recordings/0_theo_0.wav | Bin 0 -> 6328 bytes recordings/0_theo_1.wav | Bin 0 -> 5660 bytes recordings/0_theo_10.wav | Bin 0 -> 6132 bytes recordings/0_theo_11.wav | Bin 0 -> 5682 bytes recordings/0_theo_12.wav | Bin 0 -> 7278 bytes recordings/0_theo_13.wav | Bin 0 -> 6808 bytes recordings/0_theo_14.wav | Bin 0 -> 5648 bytes recordings/0_theo_15.wav | Bin 0 -> 6720 bytes recordings/0_theo_16.wav | Bin 0 -> 6820 bytes recordings/0_theo_17.wav | Bin 0 -> 6062 bytes recordings/0_theo_18.wav | Bin 0 -> 6508 bytes recordings/0_theo_19.wav | Bin 0 -> 7534 bytes recordings/0_theo_2.wav | Bin 0 -> 5508 bytes recordings/0_theo_20.wav | Bin 0 -> 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recordings/9_theo_7.wav | Bin 0 -> 7020 bytes recordings/9_theo_8.wav | Bin 0 -> 6742 bytes recordings/9_theo_9.wav | Bin 0 -> 6740 bytes 504 files changed, 186 insertions(+), 10 deletions(-) create mode 100755 acquire_data/say_numbers_prompt.py create mode 100755 acquire_data/split_and_label_numbers.py create mode 100755 recordings/0_theo_0.wav create mode 100755 recordings/0_theo_1.wav create mode 100755 recordings/0_theo_10.wav create mode 100755 recordings/0_theo_11.wav create mode 100755 recordings/0_theo_12.wav create mode 100755 recordings/0_theo_13.wav create mode 100755 recordings/0_theo_14.wav create mode 100755 recordings/0_theo_15.wav create mode 100755 recordings/0_theo_16.wav create mode 100755 recordings/0_theo_17.wav create mode 100755 recordings/0_theo_18.wav create mode 100755 recordings/0_theo_19.wav create mode 100755 recordings/0_theo_2.wav create mode 100755 recordings/0_theo_20.wav create mode 100755 recordings/0_theo_21.wav create mode 100755 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create mode 100755 recordings/9_theo_46.wav create mode 100755 recordings/9_theo_47.wav create mode 100755 recordings/9_theo_48.wav create mode 100755 recordings/9_theo_49.wav create mode 100755 recordings/9_theo_5.wav create mode 100755 recordings/9_theo_6.wav create mode 100755 recordings/9_theo_7.wav create mode 100755 recordings/9_theo_8.wav create mode 100755 recordings/9_theo_9.wav diff --git a/README.md b/README.md index bb5b625d..02745de3 100644 --- a/README.md +++ b/README.md @@ -2,11 +2,11 @@ A simple audio/speech dataset consisting of recordings of spoken digits in `wav` files at 8kHz. The recordings are trimmed so that they have near minimal silence at the beginnings and ends. -FSDD is an open dataset, which means it will grow overtime as data is contributed. Thus in order to enable reproducibility and accurate citation in scientific journals the dataset is versioned using `git tags`. +FSDD is an open dataset, which means it will grow over time as data is contributed. Thus in order to enable reproducibility and accurate citation in scientific journals the dataset is versioned using `git tags`. ### Current status -- 2 speakers -- 1,000 recordings (50 of each digit) +- 3 speakers +- 1,500 recordings (50 of each digit) - English pronunciations ### Organization @@ -14,10 +14,15 @@ Files are named in the following format: `{digitLabel}_{speakerName}_{index}.wav` Example: `7_jackson_32.wav` +### Contributions +Please contribute your homemade recordings. All recordings should be 8kHz `wav ` files and be trimmed to have minimal silence. Don't forget to update `metadata.py` with the speaker meta-data. + +To add your data, follow the recording instructions in `acquire_data/say_numbers_prompt.py` +and then run `split_and_label_numbers.py` to make your files. + ### Metadata `metadata.py` contains meta-data regarding the speakers gender and accents. - ### Included utilities `trimmer.py` Trims silences at beginning and end of an audio file. Splits an audio file into multiple audio files by periods of silence. @@ -29,17 +34,12 @@ A simple class that provides an easy to use API to access the data. Used for creating spectrograms of the audio data. Spectrograms are often a useful pre-processing step. ### Usage -The test set officially consists of the first 10% of the recordings. Recordings numbered `0-4` (inclusive) are in the test and `5-49` are in the training set. - -### Contributions -Please contribute your homemade recordings. All recordings should be 8kHz `wav ` files and be trimmed to have minimal silence. Don't forget to update `metadata.py` with the speaker meta-data. +The test set officially consists of the first 10% of the recordings. Recordings numbered `0-4` (inclusive) are in the test and `5-49` are in the training set. ### Made with FSDD Did you use FSDD in a paper, project or app? Add it here! * [https://github.com/Jakobovski/decoupled-multimodal-learning](https://github.com/Jakobovski/decoupled-multimodal-learning) - - ### License [Creative Commons Attribution-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-sa/4.0/) diff --git a/acquire_data/say_numbers_prompt.py b/acquire_data/say_numbers_prompt.py new file mode 100755 index 00000000..4233283b --- /dev/null +++ b/acquire_data/say_numbers_prompt.py @@ -0,0 +1,67 @@ +import time +import math + +""" +Prompts you to say numbers. + +Start this, and then hit "Record" in Audacity. +http://www.audacityteam.org/download/ +When you start Audacity, look in the bottom-left and set the Project Rate (Hz) to 8000. + +It takes about 30 minutes to record a full dataset. + +Tips: +- Turn off your screen saver before you start! +- Try a short recording session first to make sure everything works OK before doing the full recording. + + +When done, export the audio as one big .wav file and use 'split_and_label_numbers.py' +to make the labeled dataset. +""" + +DELAY_BETWEEN_NUMBERS = 3 +REPEATS_PER_NUMBER = 3 + + +def wait_until(t): + while time.time() < t: + time.sleep(0.01) + + +def generate_number_sequence(): + # We want the numbers jumbled up (helps eliminate any previous-number effects) + # This function scrambles the numbers in a deterministic way so that we can remember + # what the order was later. + # A deterministic shuffle makes labeling easy, makes pausing / resuming the experiment easy, etc. + nums = [str(i) for i in range(10) for set_num in range(REPEATS_PER_NUMBER)] + for i in range(len(nums)): + target = int(round(math.pi * i)) % len(nums) + (nums[i], nums[target]) = (nums[target], nums[i]) + return nums + + +def show_numbers(): + nums = generate_number_sequence() + + print "Get ready..." + time.sleep(1) + + t_start = time.time() + for i, num in enumerate(nums): + if (float(i)/len(nums) * 100) % 10 == 0: + print "\n====", float(i)/len(nums)*100, "% done====\n" + else: + print "" + + t_next_display = t_start + (i + 1) * DELAY_BETWEEN_NUMBERS + t_next_blank = t_next_display + 2.5 + + # display a number + wait_until(t_next_display) + print num + + # blank + wait_until(t_next_blank) + +if __name__ == '__main__': + show_numbers() diff --git a/acquire_data/split_and_label_numbers.py b/acquire_data/split_and_label_numbers.py new file mode 100755 index 00000000..e357446e --- /dev/null +++ b/acquire_data/split_and_label_numbers.py @@ -0,0 +1,104 @@ +import os +from collections import defaultdict + +import numpy as np +from scipy.io.wavfile import read, write + +from say_numbers_prompt import generate_number_sequence, DELAY_BETWEEN_NUMBERS + +""" +Splits up the audio data you collected in Audacity. + +Adjust the CONSTANTS below and run this file. + +Labeled audio will appear in the "recordings" dir. +""" + +YOUR_NAME_HERE = 'theo' + +# Where did you save your Audacity-exported wav file? +PATH_TO_AUDIO_FILE = r'C:\Users\theo\Desktop\spoken_numbers_R_8khz.wav' + +# Time (seconds) between the beginning of the file and the first number +# If your output files end up silent, change this number! +# It may help to look at the beginning of your recording in Audacity to see the offset. +START_OFFSET = 1.2 + +# How long it actually took you to say each number, typically 1.5 seconds +SECS_PER_NUMBER = 3 + +LABELS = generate_number_sequence() + + +def split_wav(start_offset, secs_between_numbers, secs_per_number): + fname = PATH_TO_AUDIO_FILE + rate, sound = read(fname) + + if len(sound.shape) > 1: + # Audio probably has L and R channels. + # Use the left channel only (mono). + sound = sound[:, 0] + + samples_between_numbers = int(rate * secs_between_numbers) + offset_idx = int(rate*start_offset) + + counts = defaultdict(lambda: 0) + + for i, label in enumerate(LABELS): + label = str(label) + start_idx = offset_idx + i * samples_between_numbers + stop_idx = start_idx + int(rate * secs_per_number) + + if stop_idx > len(sound): + raise('Error: Sound ends before expected number of samples reached for index:' + str(i)) + + # trim silence + digit_audio = sound[start_idx:stop_idx] + digit_audio_trimmed = trim_silence(digit_audio) + + # Build filename + outfile = label + "_" + YOUR_NAME_HERE + "_" + str(counts[label]) + ".wav" + outfile = 'recordings' + os.sep + outfile + + # Write audio chunk to file + print "writing", outfile + write(outfile, rate, digit_audio_trimmed) + counts[label] += 1 + + + +def trim_silence(audio, n_noise_samples=1000, noise_factor=1.0, mean_filter_size=100): + """ Removes the silence at the beginning and end of the passed audio data + Fits noise based on the last n_noise_samples samples in the period + Finds where the mean-filtered magnitude > noise + :param audio: numpy array of audio + :return: a trimmed numpy array + """ + start = 0 + end = len(audio)-1 + + mag = abs(audio) + + noise_sample_period = mag[end-n_noise_samples:end] + noise_threshold = noise_sample_period.max()*noise_factor + + mag_mean = np.convolve(mag, [1/float(mean_filter_size)]*mean_filter_size, 'same') + + # find onset + for idx, point in enumerate(mag_mean): + if point > noise_threshold: + start = idx + break + + # Reverse the array for trimming the end + for idx, point in enumerate(mag_mean[::-1]): + if point > noise_threshold: + end = len(audio) - idx + break + + return audio[start:end] + + +if __name__ == '__main__': + split_wav(START_OFFSET, DELAY_BETWEEN_NUMBERS, SECS_PER_NUMBER) + diff --git a/metadata.py b/metadata.py index b0737bdb..928d22af 100644 --- a/metadata.py +++ b/metadata.py @@ -10,5 +10,10 @@ 'gender': 'male', 'accent': 'BE/French', 'language': 'english' + }, + 'theo': { + 'gender': 'male', + 'accent': 'USA/neutral', + 'language': 'english' } } diff --git a/recordings/0_theo_0.wav b/recordings/0_theo_0.wav new file mode 100755 index 0000000000000000000000000000000000000000..0df72e0ccfc1b9df4643db3140d7d7ee50fef04f GIT binary patch literal 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