Using group delay functions from all-pole models for speaker recognition

Rajan P., Kinnunen T., Hanilci C., Pohjalainen J., Alku P.

14th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2013), Lyon, France, 25 - 29 August 2013, pp.2488-2492 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • City: Lyon
  • Country: France
  • Page Numbers: pp.2488-2492
  • Bursa Uludag University Affiliated: Yes


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.