Addable Stress Speech Recognition with Multiplexing HMM: Training and Non-training Decision

Author:

Amornkul Pakapong,Chamnongthai Kosin,Temdee Punnarumol

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Reference26 articles.

1. Amornkul, P., Kongkachanda, R., & Chamnongthai, K. (2001). Thai stress speech recognition with different feature extraction. In: International symposium on communication and information technology (ISCIT2001).

2. Amornkul, P., Kumhom, R., & Chamnongthai, K. (2003). Thai stress speech recognizer based on combined features. In International symposium on communication and information technology (ISCIT2003). Songkha, Thailand.

3. Amornkul, P., Kumhom, P., & Chamnongthai, K. (2005). N-best decision for thai stressed speech recognition with parallel hidden markov model. In The IEEE international symposium on intelligent signal processing and communication systems 2005 (ISPACS 2005), Hongkong.

4. Bou-Ghazale, S. E., Hansen, J. H. L., & Kaiser, J. F. (1998). Classification of speech under stress based on feature derived from the nonlinear teager energy operator. Speech Communication, 1, 549–552.

5. Chen, Y. (1987). Cepstral domain stress compensation for robust speech recognition. In IEEE international conference on acoustics, speech, signal processing (pp. 717–720).

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