9th Annual Conference of the International Speech Communication Association

Brisbane, Australia
September 22-26, 2008

Pitch Adaptive Features for LVCSR

Giulia Garau, Steve Renals

University of Edinburgh, UK

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.

Full Paper

Bibliographic reference.  Garau, Giulia / Renals, Steve (2008): "Pitch adaptive features for LVCSR", In INTERSPEECH-2008, 2402-2405.