mel-cepstral-distance 0.0.1

CLI and library to compute the Mel-Cepstral Distance of two WAV files based on the paper 'Mel-Cepstral Distance Measure for Objective Speech Quality Assessment' by Robert F. Kubichek.

Mel-Cepstral Distance

CLI and library to compute the mel-cepstral distance of two WAV files based on the paper "Mel-Cepstral Distance Measure for Objective Speech Quality Assessment" by Robert F. Kubichek.

Installation

pip install mel-cepstral-distance --user

Usage as CLI

mcd-cli

Example

# Download two example audio files
wget https://github.com/jasminsternkopf/mel_cepstral_distance/raw/main/examples/similar_audios/original.wav
wget https://github.com/jasminsternkopf/mel_cepstral_distance/raw/main/examples/similar_audios/inferred.wav

# Calculate metrics
mcd-cli original.wav inferred.wav

Output:

Mel-Cepstral Distance: 19.013673608495836
Penalty: 0.11946050096339111
# Frames: 519

This will print a message informing you about the mel-cepstral distance and penalty between the audios whose paths were given as arguments and the number of frames that were used in the computation.

Usage as a library

from mel_cepstral_distance import get_metrics_wavs, get_metrics_mels

Methods

• get_metrics_wavs
• get_metrics_mels

Both methods return the mel-cepstral distance, the penalty and the final frame number. Examples and information on the parameters can be found in the corresponding documentations.

Dependencies

• librosa >= 0.9.1
• numpy >= 1.22.3
• scipy >= 1.8.0
• fastdtw >= 0.3.4

Contributing

If you notice an error, please don't hesitate to open an issue.

Citation

If you want to cite this repo, you can use this BibTeX-entry:

@misc{stmcd22,
  author = {Sternkopf, Jasmin and Taubert, Stefan},
  title = {mel-cepstral-distance},
  year = {2022},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/jasminsternkopf/mel_cepstral_distance}}
}