python_speech_features

This library provides common speech features for ASR including MFCCs and filterbank energies.

https://github.com/jameslyons/python_speech_features

Science Score: 23.0%

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Repository

This library provides common speech features for ASR including MFCCs and filterbank energies.

Basic Info

Host: GitHub
Owner: jameslyons
License: mit
Language: Python
Default Branch: master
Homepage:
Size: 216 KB

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Stars: 2,411
Watchers: 86
Forks: 619
Open Issues: 25
Releases: 0

Created over 12 years ago · Last pushed over 4 years ago

Metadata Files

Readme License

README.rst

======================
python_speech_features
======================

This library provides common speech features for ASR including MFCCs and filterbank energies.
If you are not sure what MFCCs are, and would like to know more have a look at this 
`MFCC tutorial `_

`Project Documentation `_

To cite, please use: James Lyons et al. (2020, January 14). jameslyons/python_speech_features: release v0.6.1 (Version 0.6.1). Zenodo. http://doi.org/10.5281/zenodo.3607820

Installation
============

This `project is on pypi `_

To install from pypi:: 

	pip install python_speech_features

	
From this repository::

	git clone https://github.com/jameslyons/python_speech_features
	python setup.py develop


Usage
=====

Supported features:

- Mel Frequency Cepstral Coefficients
- Filterbank Energies
- Log Filterbank Energies
- Spectral Subband Centroids

`Example use `_

From here you can write the features to a file etc.


MFCC Features
=============

The default parameters should work fairly well for most cases, 
if you want to change the MFCC parameters, the following parameters are supported::

	python
	def mfcc(signal,samplerate=16000,winlen=0.025,winstep=0.01,numcep=13,
			 nfilt=26,nfft=512,lowfreq=0,highfreq=None,preemph=0.97,
             ceplifter=22,appendEnergy=True)

=============	===========
Parameter 		Description
=============	===========
signal			the audio signal from which to compute features. Should be an N*1 array
samplerate 		the samplerate of the signal we are working with.
winlen 			the length of the analysis window in seconds. Default is 0.025s (25 milliseconds)
winstep 		the step between successive windows in seconds. Default is 0.01s (10 milliseconds)
numcep			the number of cepstrum to return, default 13
nfilt			the number of filters in the filterbank, default 26.
nfft			the FFT size. Default is 512
lowfreq			lowest band edge of mel filters. In Hz, default is 0
highfreq		highest band edge of mel filters. In Hz, default is samplerate/2
preemph			apply preemphasis filter with preemph as coefficient. 0 is no filter. Default is 0.97
ceplifter		apply a lifter to final cepstral coefficients. 0 is no lifter. Default is 22
appendEnergy	if this is true, the zeroth cepstral coefficient is replaced with the log of the total frame energy.
returns			A numpy array of size (NUMFRAMES by numcep) containing features. Each row holds 1 feature vector.
=============	===========


Filterbank Features
===================

These filters are raw filterbank energies. 
For most applications you will want the logarithm of these features.
The default parameters should work fairly well for most cases. 
If you want to change the fbank parameters, the following parameters are supported::

	python
	def fbank(signal,samplerate=16000,winlen=0.025,winstep=0.01,
              nfilt=26,nfft=512,lowfreq=0,highfreq=None,preemph=0.97)

=============	===========
Parameter 		Description
=============	===========
signal			the audio signal from which to compute features. Should be an N*1 array
samplerate		the samplerate of the signal we are working with
winlen			the length of the analysis window in seconds. Default is 0.025s (25 milliseconds)
winstep			the step between successive windows in seconds. Default is 0.01s (10 milliseconds)
nfilt			the number of filters in the filterbank, default 26.
nfft			the FFT size. Default is 512.
lowfreq			lowest band edge of mel filters. In Hz, default is 0
highfreq		highest band edge of mel filters. In Hz, default is samplerate/2
preemph			apply preemphasis filter with preemph as coefficient. 0 is no filter. Default is 0.97
returns			A numpy array of size (NUMFRAMES by nfilt) containing features. Each row holds 1 feature vector. The second return value is the energy in each frame (total energy, unwindowed)
=============	===========


Reference
=========
sample english.wav obtained from::

	wget http://voyager.jpl.nasa.gov/spacecraft/audio/english.au
	sox english.au -e signed-integer english.wav

Owner

Name: James Lyons
Login: jameslyons
Kind: user

Repositories: 8
Profile: https://github.com/jameslyons

GitHub Events

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Watch event: 48
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Last synced: over 2 years ago

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Total Commits: 102
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Avg Commits per committer: 5.368
Development Distribution Score (DDS): 0.373

Past Year

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Committers: 0
Avg Commits per committer: 0.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
James Lyons	j**0@g**m	64
scienceopen	s****n	11
ybdarrenwang	d**g@f**m	7
Yow-Bang (Darren) Wang	y**g@g**m	2
janLuke	g**o@g**m	2
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hshteingart	h**t@s**m	2
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Watcharapol Watcharawisetkul	g**l@g**m	1
Yash Gaurkar	y**r@g**m	1
erikma	e**1@h**m	1
Chris Lord	c**t@g**m	1
Adam Stark	a**k@g**m	1
Sam Birch	s**h@g**m	1
Lu ZhiHe	l**e@g**m	1
Tim Gates	t**s@i**m	1

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Issues and Pull Requests

Last synced: 11 months ago

All Time

Total issues: 71
Total pull requests: 29
Average time to close issues: 4 months
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Total packages: 2
Total downloads:
- pypi 51,323 last-month
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Total dependent packages: 2
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Total dependent repositories: 244
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Total versions: 7
Total maintainers: 1

pypi.org: python_speech_features

Python Speech Feature extraction

Homepage: https://github.com/jameslyons/python_speech_features
Documentation: https://python_speech_features.readthedocs.io/
License: MIT
Latest release: 0.6
published almost 9 years ago

Versions: 6
Dependent Packages: 2
Dependent Repositories: 244
Downloads: 51,323 Last month
Docker Downloads: 27

Rankings

Downloads: 0.8%

Dependent repos count: 1.0%

Stargazers count: 1.5%

Forks count: 1.9%

Average: 2.3%

Docker downloads count: 4.1%

Dependent packages count: 4.8%

Maintainers (1)

james.lyons

Last synced: 11 months ago

proxy.golang.org: github.com/jameslyons/python_speech_features

Documentation: https://pkg.go.dev/github.com/jameslyons/python_speech_features#section-documentation
License: mit
Latest release: v0.6.0
published over 7 years ago

Versions: 1
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 5.5%

Average: 5.7%

Dependent repos count: 5.9%

Last synced: 11 months ago

Dependencies

requirements.txt pypi

mock *

setup.py pypi

numpy *
scipy *

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python_speech_features

Science Score: 23.0%

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