论文信息 - Using Second-Order Hidden Markov Models to Enhance Speaker Authentication Performance

Using Second-Order Hidden Markov Models to Enhance Speaker Authentication Performance

In this paper, the second-order hidden Markov models (HMM2s) have been used to enhance the recognition performance of isolated -word text -dependent speaker authentication systems under the neutral talking condition. Our results show that HMM2s enhance the speaker authentication performance under such a condition compared to the first- order hidden Markov models (HMM1s). The speaker authentication performance has been improved by 6%.

Ismail Shahin | United Arab Emirates

[1] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[2] L. R. Rabiner,et al. On the application of vector quantization and hidden Markov models to speaker-independent, isolated word recognition , 1983, The Bell System Technical Journal.

[3] Jianing Dai. Isolated word recognition using Markov chain models , 1995, IEEE Trans. Speech Audio Process..

[4] Biing-Hwang Juang,et al. Hidden Markov Models for Speech Recognition , 1991 .

[5] Jean-François Mari,et al. A second-order HMM for high performance word and phoneme-based continuous speech recognition , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[6] Abdelaziz Kriouile,et al. Automatic word recognition based on second-order hidden Markov models , 1994, IEEE Trans. Speech Audio Process..

[7] Thomas Quatieri,et al. Discrete-Time Speech Signal Processing: Principles and Practice , 2001 .

[8] Ismail Shahin,et al. Text-dependent speaker identification using hidden Markov model with stress compensation technique , 1998, Proceedings IEEE Southeastcon '98 'Engineering for a New Era'.