Convert WAV files to Mel spectrograms
Project description
wav2mel
Converts WAV audio [1] to Mel spectrograms for use in machine learning systems like Tacotron2.
This library contains portions of the copy-pasted code you see everywhere for WAV to Mel conversion.
[1] Or any audio format supported by librosa (which uses soundfile and audioread).
Installation
pip install wav2mel
Dependencies
- Python 3.6 or higher
- librosa, numpy, scipy, numba
Format
wav2mel
outputs numpy save data: one .npy
file each input file.
Usage
You can convert a single WAVE file from .wav
to a mel spectrogram (.npy
) as follows:
wav2mel < WAVE_FILE > NPY_FILE
Multiple WAVE files can also be converted and saved to a directory:
wav2mel --output-dir /path/to/mels WAVE_FILE [WAVE_FILE ...]
Each .npy
file will be named after the corresponding .wav
file.
See wav2mel --help
for more options (filter/hop/window length, sample rate, etc.).
With GNU Parallel
find /path/to/wavs -name '*.wav' -type f | parallel -X wav2mel --output-dir /path/to/mels
mel2wav (Griffin-Lim)
You can convert a mel spectrogram to WAV audio too using griffin-lim:
mel2wav < NPY_FILE > WAVE_FILE
or
mel2wav --output-dir /path/to/wavs NPY_FILE [NPY_FILE ...]
See mel2wav --help
for more options.
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