Resumo

REYES DIAZ, Flavio J.; HERNANDEZ SIERRA, Gabriel  e  CALVO DE LARA, José. A Gaussian Selection Method for Speaker Verification with Short Utterances. Comp. y Sist. [online]. 2014, vol.18, n.2, pp.345-358. ISSN 2007-9737.  https://doi.org/10.13053/CyS-18-2-2014-036.

Speaker recognition systems frequently use GMM-MAP method for modeling speakers. This method represents the speaker using a Gaussian mixture. However, in this mixture not all Gaussian components are truly representative of the speaker. In order to remove the model redundancy, this work proposes a Gaussian selection method to achieve a new GMM model only with the more representative Gaussian components. The results of speaker verification experiments applying the proposal show a similar performance to the baseline; however, the speaker models used have a reduction of 80% compared to the speaker model used as the baseline. Our proposal was also applied to speaker recognition system with short test signals of 15, 5 and 3 seconds obtaining an improvement in EER of 0.43%, 2.64% and 1.60%, respectively, compared to the baseline. The application of this method in real or embedded speaker verification systems could be very useful for reducing computational and memory cost.

Palavras-chave : Speaker verification; Gaussian components selection; cumulative vector; short utterance.

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