https://github.com/RicherMans/PLDA
An LDA/PLDA estimator using KALDI in python for speaker verification tasks
https://github.com/RicherMans/PLDA
kaldi plda speaker-verification
Last synced: about 1 year ago
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An LDA/PLDA estimator using KALDI in python for speaker verification tasks
- Host: GitHub
- URL: https://github.com/RicherMans/PLDA
- Owner: RicherMans
- Created: 2015-10-04T08:52:43.000Z (over 10 years ago)
- Default Branch: master
- Last Pushed: 2017-04-15T03:13:21.000Z (about 9 years ago)
- Last Synced: 2024-11-17T22:35:00.198Z (over 1 year ago)
- Topics: kaldi, plda, speaker-verification
- Language: Python
- Size: 149 KB
- Stars: 99
- Watchers: 10
- Forks: 24
- Open Issues: 2
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Metadata Files:
- Readme: README
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README
=== A simple library to run LDA ===
With this library LDA can be run. The library provides overall just two simple methods to estimate
and predict an LDA classifier.
=== Installation ===
Make sure you have the variable KALDI_ROOT set in your path.
Otherwise:
export KALDI_ROOT=/YOUTPATH/TO/KALDI/ROOT
then just build the libraries:
mkdir build
cd build
cmake ../
make
The installation process compiles a shared library and drops it into the local users python path.
To use it, please just write any python script:
import liblda
lda = liblda.LDA()
#Estimate an LDA model
lda.fit(spktoutts,targetdim)
transformedutt = lda.fit(pathtoutt)
Make sure that spktoutts is a dict where the keys represent the speaker model and the values
represent all the utterances belonging to that speaker. Therefore it is a dict with strings
as keys and a list as values.