Abstract
The paper presents a speaker detection system based on phoneme specific hidden Markov model in combination with Gaussian mixture model. Our motivation stems from the fact that the phoneme specific HMM system can model temporal variations and provides possibility to ponder the scores of specific phonemes as well as efficient pruning. The performance of the system has been evaluated on speech database which contains utterances in Serbian from 250 speakers (10 of them being the target speakers). The proposed model is compared to a system based on Gaussian mixture model - universal background model, and showed a significant improvement in detection performance.
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Pakoci, E., Jakovljević, N., Popović, B., Mišković, D., Pekar, D. (2014). Speaker Detection Using Phoneme Specific Hidden Markov Models. In: Ronzhin, A., Potapova, R., Delic, V. (eds) Speech and Computer. SPECOM 2014. Lecture Notes in Computer Science(), vol 8773. Springer, Cham. https://doi.org/10.1007/978-3-319-11581-8_51
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DOI: https://doi.org/10.1007/978-3-319-11581-8_51
Publisher Name: Springer, Cham
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