Title :
Emerging features for speaker recognition
Author :
Ambikairajah, Eliathamby
Author_Institution :
Univ. of New South Wales, Sydney
Abstract :
Cepstral features and their derivatives have been successfully used in speaker recognitions tasks over the past two decades. Recently new features are emerging that make use of information that is not contained in cepstral features or their derivative, namely the phase spectra and instantaneous frequency. There are numerous approaches to capture instantaneous amplitude and frequency variations in the signal, resulting in an amplitude and frequency modulation (AM-FM) feature set. While the addition of modulation features has been shown to improve speech recognition systems based on cepstral features, their use in speaker recognition is new and has not been fully explored. This paper outlines some of these emerging features and their extraction methods for use in speaker recognition tasks. The paper also talks about the recently proposed Empirical Mode Decomposition (EMD) as an alternative method of extracting instantaneous frequency.
Keywords :
amplitude modulation; feature extraction; frequency modulation; speaker recognition; Empirical Mode Decomposition; amplitude modulation; cepstral feature extraction; frequency modulation; speaker recognition; Australia; Band pass filters; Cepstral analysis; Communications technology; Delay estimation; Fourier transforms; Frequency modulation; Speaker recognition; Speech analysis; Speech synthesis; AM-FM; cepstral features; empirical mode decomposition; group delay; modulation features; phase spectra;
Conference_Titel :
Information, Communications & Signal Processing, 2007 6th International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-0982-2
Electronic_ISBN :
978-1-4244-0983-9
DOI :
10.1109/ICICS.2007.4449889