Shennong provides a wide range of speech features extraction algorithms as well as post-processing pipelines. It relies on Kaldi for most of the algorithms while providing simple to use Python API and command line interface.
-
See the complete documentation at https://docs.cognitive-ml.fr/shennong.
-
See the detailed installation procedure here. On Linux, simply have a:
conda install -c coml -c conda-forge shennong -
Implementented models include filterbanks, MFCC, PLP, bottleneck, pitch, delta, CMVN, VAD, VTLN. See the complete list of available features here.
-
To reference Shennong in your own work, please cite the following Behavior Research Methods paper which is also available on arXiv:
@article{bernard2023shennong,
title = {Shennong: {{A Python}} Toolbox for Audio Speech Features Extraction},
author = {Bernard, Mathieu and Poli, Maxime and Karadayi, Julien and Dupoux, Emmanuel},
year = {2023},
journal = {Behavior Research Methods},
url = {https://doi.org/10.3758/s13428-022-02029-6},
doi = {10.3758/s13428-022-02029-6},
}