An extensible speaker identification sidekit in Python

SIDEKIT is a new open-source Python toolkit that includes a large panel of state-of-the-art components and allow a rapid prototyping of an end-to-end speaker recognition system. For each step from front-end feature extraction, normalization, speech activity detection, modelling, scoring and visualiz...

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Bibliographic Details
Published in2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 5095 - 5099
Main Authors Larcher, Anthony, Lee, Kong Aik, Meignier, Sylvain
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 01.03.2016
Subjects
Algorithms
Electronics
Feature extraction
Open source software
open-source
Panels
python
Source code
Speaker recognition
Speech
toolkit
Tutorials
Visualization
Online AccessGet full text
ISSN2379-190X
DOI10.1109/ICASSP.2016.7472648

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Summary:SIDEKIT is a new open-source Python toolkit that includes a large panel of state-of-the-art components and allow a rapid prototyping of an end-to-end speaker recognition system. For each step from front-end feature extraction, normalization, speech activity detection, modelling, scoring and visualization, SIDEKIT offers a wide range of standard algorithms and flexible interfaces. The use of a single efficient programming and scripting language (Python in this case), and the limited dependencies, facilitate the deployment for industrial applications and extension to include new algorithms as part of the whole tool-chain provided by SIDEKIT. Performance of SIDEKIT is demonstrated on two standard evaluation tasks, namely the RSR2015 and NIST-SRE 2010.
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ISSN:2379-190X
DOI:10.1109/ICASSP.2016.7472648