On leveraging conversational data for building a text dependent speaker verification system

Hagai Aronowitz, Oren Barkan

Research output: Contribution to journalConference articlepeer-review

Abstract

Recently we have investigated the use of state-of-the-art textindependent and text-dependent speaker verification algorithms for a text-dependent user authentication task and obtained satisfactory results mainly by using a fair amount of text-dependent development data. In our study, best results were obtained using the NAP framework rather than using the more advanced JFA and i-vector-based frameworks. In this work we investigate the ability to build high accuracy i-vectorbased systems by leveraging widely available conversational data. We explore various techniques for transforming conversational sessions in such a way that attributes which are more relevant to the text-dependent task are enhanced. Using these techniques we managed to reduce verification error significantly.

Original languageEnglish
Pages (from-to)2470-2473
Number of pages4
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
StatePublished - 2013
Event14th Annual Conference of the International Speech Communication Association, INTERSPEECH 2013 - Lyon, France
Duration: 25 Aug 201329 Aug 2013

Keywords

  • Speaker verification
  • Text-dependent
  • Transfer learning

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modelling and Simulation

Fingerprint

Dive into the research topics of 'On leveraging conversational data for building a text dependent speaker verification system'. Together they form a unique fingerprint.

Cite this