Using group delay functions from all-pole models for speaker recognition
P.K. Rajan, Tomi Kinnunen, Cemal Hanilçi, Jouni Pohjalainen, Paavo Alku · 2013
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 un-used. While the common argument to use only the magnitude spectrum is that the human ear is phase-deaf, phase-based fea-tures have remained less explored due to additional signal pro-cessing difficulties they introduce. A useful representation of the phase is the group delay function, but its robust computa-tion 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 recog-nition accuracy, especially under high vocal effort. Addition-ally, 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. Index Terms: speaker verification, group delay functions, high vocal effort