Combining stochastic feature transformation and handset identification for telephone-based speaker verification

Man Wai Mak, Sun Yuan Kung

Research output: Journal article publicationConference articleAcademic researchpeer-review

25 Citations (Scopus)


The performance of telephone-based speaker verification systems can be severely degraded by the acoustic mismatch caused by telephone handsets. This paper proposes to combine a handset selector with stochastic feature transformation to reduce the mismatch. Specifically, a GMM-based handset selector is trained to identify the most likely handset used by the claimants, and then handset-specific stochastic feature transformations are applied to the distorted feature vectors. To overcome the non-linear distortion introduced by telephone handsets, a 2nd-order stochastic feature transformation is proposed. Estimation algorithms based on the stochastic matching technique and the EM algorithm are derived. Experimental results based on 150 speakers of the HTIMIT corpus show that the handset selector is able to identify the handsets accurately (98.3%), and that both linear and non-linear transformation reduce the error rate significantly (from 12.37% to 5.49%).
Original languageEnglish
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publication statusPublished - 11 Jul 2002
Event2002 IEEE International Conference on Acustics, Speech, and Signal Processing - Orlando, FL, United States
Duration: 13 May 200217 May 2002

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


Dive into the research topics of 'Combining stochastic feature transformation and handset identification for telephone-based speaker verification'. Together they form a unique fingerprint.

Cite this