14thAnnual Conference of the International Speech Communication Association

Lyon, France
August 25-29, 2013

Using Group Delay Functions from All-Pole Models for Speaker Recognition

Padmanabhan Rajan (1), Tomi Kinnunen (1), Cemal Hanilçi (2), Jouni Pohjalainen (3), Paavo Alku (3)

(1) University of Eastern Finland, Finland
(2) Uludağ Üniversitesi, Turkey
(3) Aalto University, Finland

Popular features for speech processing, such as mel-frequency cepstral coefficients (MFCCs), are derived from the short-term magnitude spectrum, whereas the phase spectrum remains unused. While the common argument to use only the magnitude spectrum is that the human ear is phase-deaf, phase-based features have remained less explored due to additional signal processing difficulties they introduce. A useful representation of the phase is the group delay function, but its robust computation remains difficult. This paper advocates the use of group delay functions derived from parametric all-pole models instead of their direct computation from the discrete Fourier transform. Using a subset of the vocal effort data in the NIST 2010 speaker recognition evaluation (SRE) corpus, we show that group delay features derived via parametric all-pole models improve recognition accuracy, especially under high vocal effort. Additionally, the group delay features provide comparable or improved accuracy over conventional magnitude-based MFCC features. Thus, the use of group delay functions derived from all-pole models provide an effective way to utilize information from the phase spectrum of speech signals.

Full Paper

Bibliographic reference.  Rajan, Padmanabhan / Kinnunen, Tomi / Hanilçi, Cemal / Pohjalainen, Jouni / Alku, Paavo (2013): "Using group delay functions from all-pole models for speaker recognition", In INTERSPEECH-2013, 2489-2493.