Improving Speaker Identification Performance Under the Shouted Talking Condition Using the Second-Order Hidden Markov Models

Speaker identification systems perform well under the neutral talking condition; however, they suffer sharp degradation under the shouted talking condition. In this paper, the second-order hidden Markov models (HMM2s) have been used to improve the recognition performance of isolated-word text-dependent speaker identification systems under the shouted talking condition. Our results show that HMM2s significantly improve the speaker identification performance compared to the first-order hidden Markov models (HMM1s). The average speaker identification performance under the shouted talking condition based on HMM1s is. On the other hand, the average speaker identification performance based on HMM2s is.

[1]  Yeunung Chen,et al.  Cepstral domain talker stress compensation for robust speech recognition , 1988, IEEE Trans. Acoust. Speech Signal Process..

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

[3]  D Cairns,et al.  NONLINEAR ANALYSIS AND DETECTION OF SPEECH UNDER STRESSED CONDITIONS , 1994 .

[4]  K E Cummings,et al.  Analysis of the glottal excitation of emotionally styled and stressed speech. , 1995, The Journal of the Acoustical Society of America.

[5]  John H. L. Hansen,et al.  Nonlinear feature based classification of speech under stress , 2001, IEEE Trans. Speech Audio Process..

[6]  John H. L. Hansen,et al.  Analysis and compensation of speech under stress and noise for environmental robustness in speech recognition , 1996, Speech Commun..

[7]  John H. L. Hansen,et al.  A comparative study of traditional and newly proposed features for recognition of speech under stress , 2000, IEEE Trans. Speech Audio Process..

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

[9]  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'.

[10]  Ismail Shahin.  Using second-order hidden Markov model to improve speaker identification recognition performance under neutral condition , 2003, 10th IEEE International Conference on Electronics, Circuits and Systems, 2003. ICECS 2003. Proceedings of the 2003.

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

[12]  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.

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