https://github.com/nanahou/LPS_extraction

The script is to extract log-power-spectrum features for speech enhancement and bandwidth extension.
https://github.com/nanahou/LPS_extraction

Last synced: 14 days ago
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The script is to extract log-power-spectrum features for speech enhancement and bandwidth extension.

• Host: GitHub
• URL: https://github.com/nanahou/LPS_extraction
• Owner: nanahou
• Created: 2020-02-04T08:47:46.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2020-06-11T02:00:46.000Z (over 4 years ago)
• Last Synced: 2024-08-02T07:20:04.873Z (4 months ago)
• Language: Python
• Size: 2.47 MB
• Stars: 5
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• Awesome-Speech-Enhancement - LPS - power-spectrum/magnitude spectrum/log-magnitude spectrum/Cepstral mean and variance normalization. | (Tools / Coming soon...)

README

        
# LPS_extraction

============================================

The script is to extract log-power-spectrum (LPS) for speech enhancement and bandwidth extension.

### Requirements

The model is implemented in PyTorch and uses several additional libraries. Specifically, we used:

* `pytorch==1.0`

* `python==3.6.8`

* `numpy==1.15.4`

* `scipy==1.2.0`

### Setup

To install this package, simply clone the git repo:

```

git clone https://github.com/nanahou/LPS_extraction.git;

cd LPS_extraction;

```

### Contents

The repository is structured as follows.

* `./data`: some audio samples from dataset[1]

* `audioread.py`: the function to read audios

* `extract_LPS.py`: the main scripts to extract features

* `normhamming.py`: the function to apply a normalized square root hamming periodic window 

* `plot_spectrum.py`: the function to plot the LPS features

* `sigproc.py`: including the functions to frame signals, deframe signals from [2]

### Usage

* If extracting LPS features, you only need to replace the path in `extract_LPS.py` with your own data path and run: 

  ```python extract_LPS.py```

* If plotting your features, you only need to call the function in `plot_spectrum.py`.

### Reference

```

[1]. Valentini-Botinhao, C., Wang, X., Takaki, S. and Yamagishi, J., 2016. Speech Enhancement for a Noise-Robust Text-to-Speech Synthesis System Using Deep Recurrent Neural Networks. In Interspeech (pp. 352-356).

[2]. https://github.com/jameslyons/python_speech_features/blob/master/python_speech_features/sigproc.py

```