Python_Kaldi_Feature

The Kaldi Feature Written by Python

Extractor Feature

Please see the featurebin/.

You should change the conf/ and write a .ini file as a config file. Note that you can write in several settings into one .ini and you can use config_section to

You should first prepare the wav.scp for the project which is similar with Kaldi

Note that the project do not support the pipe data for extracting features!

I will add this function in the following version

The project will write to some *.ark files and a feats.scp. The features the project get will not be compressed, however, you can use the feature_reader code to read the kaldi feature.

The Kaldi features compress is irreversible which means you cannot get the features before compressing, if you use wsj/steps/make_mfcc.sh, etc., the compress parameter is always true unless you change it, there're no plan to add compress functions).

Project Structure and Details

Pytorch API

Please see the torch_feature/ and use the feature_kernels. The torch-api for computing the feature more quickly and you can insert the feature-extractor into the model, and you can even train them as I provide the requires_grad!

Difference between Kaldi

1. DO NOT realize the dither for each, you can see the function but we will not use that, which may cause the great difficulty for debugging.

2. DO NOT do the vltn part in our projects, so when we will get the single instance for mel_banks

3. Use more value-call for the functions instead of reference-call, which is simpler for python programming. So you can see there're less assert to check the dim problems.

To-do List

1. Add pitches
2. Merge more functions into one function, such as computer power spectrogram
3. Add PLP features
4. Use Subprocess to let the wav can be a pipe data
5. Add multiprocess part to improve the effectiveness
6. More useful verbose and logging code
7. Tensorflow support
8. Compare with torchaudio

Please give me more suggestions and help improvement! You can email me and ask any questions in issue!

Reference

• Kaldi
• The kaldi-io code is from kaldi-python-io