Prosodic Features-Based Speaker Verification Using Speaker-Specific-Text For Short Utterances

Over the past several years, Gaussian mixture model and its variants have been dominant architectures in text-independent and text-dependent speaker recognition field. The recognition accuracy of above-mentioned models declines when experimental utterances' length becomes short in practical application. Presently, Mel-frequency cepstral coefficients are generally used to characterise the properties of the vocal tract and widely applied in speech recognition. In addition, prosodic features, such as pitch and formant, are generally considered to describe the glottal characteristics. However, the efficiency of those approaches remains unsatisfactory. In text-dependent short utterance speaker verification systems, prosodic features can assist to improve the recognition result theoretically. In order to optimise the performance of speaker verification systems under the framework of adapted GMM-UBM, we adopt a variant speaker verification system based on prosodic features, in which a dual judgement mechanism is used in order to integrate vocal tract features with prosodic features. Experimental results showed that the new speech recognition system gives a better consequence.