Unsupervised speaker segmentation in telephone conversations

Arnon Cohen, Vladimir Lapidus

Research output: Contribution to conferencePaperpeer-review

8 Scopus citations

Abstract

Speaker recognition and verification has been used in a variety of commercial, forensic and military applications. The classical problem is that of supervised recognition, in which there is sufficient a priori information on the speakers to be identified. This paper deals with the problem of unsupervised speech segmentation and speaker classification, where no a priori speaker information is available. The algorithm accepts dual-speaker conversation telephone speech data, detects events of simultaneous speakers, and segment the signal by assigning each speech segment to its speaker. Discrete HMM are used, with 12th order cepstral coefficients. Correct recognition rates of more than 90% are demonstrated.

Original languageEnglish
Pages102-105
Number of pages4
StatePublished - 1 Dec 1996
EventProceedings of the 1996 19th Convention of Electrical and Electronics Engineers in Israel - Jerusalem, Isr
Duration: 5 Nov 19966 Nov 1996

Conference

ConferenceProceedings of the 1996 19th Convention of Electrical and Electronics Engineers in Israel
CityJerusalem, Isr
Period5/11/966/11/96

ASJC Scopus subject areas

  • Engineering (all)

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