PYTHON WORLD VOCODER:

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This is a line-by-line implementation of WORLD vocoder (Matlab, C++) in python. It supports python 3.0 and later.

INSTALLATION

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Clone this repository and install with:

python -m pip install -e .  

EXAMPLE

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import worldvocoder as wv
import soundfile as sf
import librosa

# read audio
audio, sample_rate = sf.read("some_file.wav")
audio = librosa.to_mono(audio)

# initialize vocoder
vocoder = wv.World()

# encode audio
dat = vocoder.encode(sample_rate, audio, f0_method='harvest')

in which, sample_rate is sampling frequency and audio is the speech/singing signal.

The dat is a dictionary object that contains pitch, magnitude spectrum, and aperiodicity.

We can scale the pitch:

dat = vocoder.scale_pitch(dat, 1.5)

Be careful when you scale the pich because there is upper limit and lower limit.

We can make speech faster or slower:

dat = vocoder.scale_duration(dat, 2)

To resynthesize the audio:

dat = vocoder.decode(dat)
output = dat["out"]

To use d4c_requiem analysis and requiem_synthesis in WORLD version 0.2.2, set the variable is_requiem=True:

# requiem analysis
dat = vocoder.encode(fs, x, f0_method='harvest', is_requiem=True)

To extract log-filterbanks, MCEP-40, VAE-12 as described in the paper Using a Manifold Vocoder for Spectral Voice and Style Conversion, check test/spectralFeatures.py. You need Keras 2.2.4 and TensorFlow 1.14.0 to extract VAE-12. Check out speech samples

NOTE:

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• The vocoder use pitch-synchronous analysis, the size of each window is determined by fundamental frequency F0. The centers of the windows are equally spaced with the distance of frame_period ms.

• The Fourier transform size (fft_size) is determined automatically using sampling frequency and the lowest value of F0 f0_floor. When you want to specify your own fft_size, you have to use f0_floor = 3.0 * fs / fft_size. If you decrease fft_size, the f0_floor increases. But, a high f0_floor might be not good for the analysis of male voices.

CITATION:

Dinh, T., Kain, A., & Tjaden, K. (2019). Using a manifold vocoder for spectral voice and style conversion. Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 2019-September, 1388-1392.