Speaker Recognition Using Syllable-Based Constraints for Cepstral Frame Selection


T. Bocklet and E. Shriberg, “Speaker recognition using syllable-based constraints for cepstral frame selection,” 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009, pp. 4525-4528, doi: 10.1109/ICASSP.2009.4960636.


We describe a new GMM-UBM speaker recognition system that uses standard cepstral features, but selects different frames of speech for different subsystems. Subsystems, or ldquoconstraintsrdquo, are based on syllable-level information and combined at the score level. Results on both the NIST 2006 and 2008 test data sets for the English telephone train and test condition reveal that a set of eight constraints performs extremely well, resulting in better performance than other commonly-used cepstral models. Given the still largely-unexplored world of possible constraints and combinations, it is likely that the approach can be even further improved.

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