svm_training
Copyright 2014-2015 Anthony Larcher
svm_training provides utilities to train Support Vector Machines
to perform speaker verification.
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svm_training.svm_training(svmDir, background_sv, enroll_sv, numThread=1)[source]
Train Suport Vector Machine classifiers for two classes task
(as implemented for nowbut miht change in the future to include multi-class
classification)
Training is parallelized on multiple threads.
Parameters: |
- svmDir – directory where to store the SVM models
- background_sv – StatServer of super-vectors for background impostors. All
super-vectors are used without selection
- enroll_sv – StatServer of super-vectors used for the target models
- numThread – number of thread to launch in parallel
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svm_training.svm_training_singleThread(K, msn, bsn, svmDir, background_sv, models, enroll_sv)[source]
Train Suport Vector Machine classifiers for two classes task
(as implemented for nowbut miht change in the future to include multi-class
classification)
Parameters: |
- K – pre-computed part of the Gram matrix
- msn – maximum number of sessions to train a SVM
- bsn – number of session used as background impostors
- svmDir – directory where to store the SVM models
- background_sv – StatServer of super-vectors for background impostors. All
super-vectors are used without selection
- models – list of models to train. The models must be included in the
enroll_sv StatServer
- enroll_sv – StatServer of super-vectors used for the target models
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