Application of Auditory Representations on Speaker Identification

Title of Thesis: APPLICATION OF AUDITORY REPRESENTATIONS ON SPEAKER IDENTIFICATION The noise-robustness of auditory spectrum and cortical representation is examined by applying to text-independent speaker identiication tasks. A Bayes classiier residing on M-ary hypothesis test is employed to evaluate the robust-ness of the auditory cepstrum and demonstrate its superior performance to that of the well-studied mel-cepstrum. In addition, the phase feature of the wavelet-transform based multiscale cortical representation is shown much more stable than magnitude feature in characterizing speakers by correlator technique which is traditionally used in scene matching application. This observation bears con-sistence to physiological and psychoacoustic phenomena. The underlying purpose of this study is to inspect the inherent robustness of the auditory representations which are derived from a human perception based model. The experimental results indicate that the biologically motivated features signiicantly enhance the speaker identiication accuracy under noisy environments .

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