Abstract
The information of the vocal tract and the glottis are two kinds of sources which can characterize speakers. Though the former one has archived quite good performance in automatic speaker recognition (ASR) tasks, the glottal information behaves poorly when used individually. This work explores how to combining vocal tract and glottal information in an efficient and effective way. Taking into account the short-term correlation between them, our improved joint probability function model of the corresponding features is first proposed. Then we present a novel integrating system which uses parallel Gaussian Mixture Models (GMM) grounded on this function. Together with the traditional GMM, it also forms a hybrid model. Both methods were applied to YOHO and SRMC corpus, and experimental works show promising results.
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Yang, P., Yang, Y., Wu, Z. (2005). Exploiting Glottal Information in Speaker Recognition Using Parallel GMMs. In: Kanade, T., Jain, A., Ratha, N.K. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2005. Lecture Notes in Computer Science, vol 3546. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527923_84
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DOI: https://doi.org/10.1007/11527923_84
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