Unsupervised speaker classification using self-organizing maps (SOM)

Itshak Voitovetsky, Hugo Guterman, Arnon Cohen

Research output: Contribution to conferencePaperpeer-review

12 Scopus citations

Abstract

An algorithm for unsupervised speaker classification using Kohonen SOM is presented. The system employs 6×10 SOM networks for each speaker and for non-speech segments. The algorithm was evaluated using high quality as well as telephone quality conversations between two speakers. Correct classification of more than 90% was demonstrated. High quality conversation between three speakers yielded 80% correct classification. The high quality speech required the use of 12th order cepstral coefficients vector. In telephone quality speech, additional 12 features of the difference of the cepstrum were required.

Original languageEnglish
Pages578-587
Number of pages10
StatePublished - 1 Dec 1997
EventProceedings of the 1997 7th IEEE Workshop on Neural Networks for Signal Processing, NNSP'97 - Amelia Island, FL, USA
Duration: 24 Sep 199726 Sep 1997

Conference

ConferenceProceedings of the 1997 7th IEEE Workshop on Neural Networks for Signal Processing, NNSP'97
CityAmelia Island, FL, USA
Period24/09/9726/09/97

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

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