Pitch adaptive features for LVCSR

Giulia Garau, Steve Renals

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We have investigated the use of a pitch adaptive spectral representation on large vocabulary speech recognition, in conjunction with speaker normalisation techniques. We have compared the effect of a smoothed spectrogram to the pitch adaptive spectral analysis by decoupling these two components of STRAIGHT. Experiments performed on a large vocabulary meeting speech recognition task highlight the importance of combining a pitch adaptive spectral representation with a conventional fixed window spectral analysis. We found evidence that STRAIGHT pitch adaptive features are more speaker independent than conventional MFCCs without pitch adaptation, thus they also provide better performances when combined using feature combination techniques such as Heteroscedastic Linear Discriminant Analysis.
Original languageEnglish
Title of host publicationINTERSPEECH 2008
Subtitle of host publication9th Annual Conference of the International Speech Communication Association
Publication statusPublished - 2008
EventINTERSPEECH 2008 - 9th Annual Conference of the International Speech Communication Association - Brisbane, Australia
Duration: 22 Sep 200826 Sep 2008

Conference

ConferenceINTERSPEECH 2008 - 9th Annual Conference of the International Speech Communication Association
CountryAustralia
CityBrisbane
Period22/09/0826/09/08

Fingerprint Dive into the research topics of 'Pitch adaptive features for LVCSR'. Together they form a unique fingerprint.

Cite this