ISCA Archive Interspeech 2005
ISCA Archive Interspeech 2005

Gaussian mixture modelling of broad phonetic and syllabic events for text-independent speaker verification

Brendan Baker, Robbie Vogt, Sridha Sridharan

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.


doi: 10.21437/Interspeech.2005-648

Cite as: Baker, B., Vogt, R., Sridharan, S. (2005) Gaussian mixture modelling of broad phonetic and syllabic events for text-independent speaker verification. Proc. Interspeech 2005, 2429-2432, doi: 10.21437/Interspeech.2005-648

@inproceedings{baker05_interspeech,
  author={Brendan Baker and Robbie Vogt and Sridha Sridharan},
  title={{Gaussian mixture modelling of broad phonetic and syllabic events for text-independent speaker verification}},
  year=2005,
  booktitle={Proc. Interspeech 2005},
  pages={2429--2432},
  doi={10.21437/Interspeech.2005-648}
}