Speaker identification using radial basis functions

Man Wai Mak, W. G. Allen, G. G. Sexton

Research output: Journal article publicationConference articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

This paper describes a text-independent speaker identification system based on Radial Basis Functions (RBF) networks. Both text-dependent and text-independent speaker identification experiments have been conducted. The database contains 7 sentences and 10 digits spoken by 20 speakers over a period of 9 months. LPC-derived cepstrum coefficients are used as the speaker specific features. The results show that RBF networks offer fast learning speed and good generalization even in text-independent mode. Moreover, a robustness test has been carried out which demonstrates that RBF networks provide sufficient information to produce a `no match' decision in speaker identification applications.
Original languageEnglish
Pages (from-to)138-141
Number of pages4
JournalIEE Conference Publication
Issue number372
Publication statusPublished - 1 Jan 1993
Externally publishedYes
Event3rd International Conference on Artificial Neural Networks - Brighton, United Kingdom
Duration: 25 May 199327 May 1993

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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