Interspeech'2005 - Eurospeech

Lisbon, Portugal
September 4-8, 2005

Gaussian Mixture Modelling of Broad Phonetic and Syllabic Events for Text-Independent Speaker Verification

Brendan Baker, Robbie Vogt, Sridha Sridharan

Queensland University of Technology, Australia

This paper examines the usefulness of a multilingual broad syllable-based framework for text-independent speaker verification. Syllabic segmentation is used in order to obtain a convenient unit for constrained and more detailed model generation. Gaussian mixture models are chosen as a suitable modelling paradigm for initial testing of the framework. Promising results are presented for the NIST 2003 speaker recognition evaluation corpus. The syllable-based modelling technique is shown to outperform a state-of-the-art baseline GMM system. A simple selective reduction of the syllable set is also shown to give further improvement in performance. Overall, the syllable based framework presents itself as valid alternative to text-constrained speaker verification systems, with the advantage of being multilingual. The framework allows for future testing of alternative modelling paradigms, feature sets and qualitative analysis.

Full Paper

Bibliographic reference.  Baker, Brendan / Vogt, Robbie / Sridharan, Sridha (2005): "Gaussian mixture modelling of broad phonetic and syllabic events for text-independent speaker verification", In INTERSPEECH-2005, 2429-2432.