HMM/SVM segmentation and labelling of Arabic speech for speech recognition applications

Author:

Frihia Hamza,Bahi HalimaORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Vision and Pattern Recognition,Linguistics and Language,Human-Computer Interaction,Language and Linguistics,Software

Reference48 articles.

1. Abdo, M. S., & Kandil, A. H. (2016). Semi-automatic segmentation system for syllables extraction from continuous Arabic audio signal. International Journal of Advanced Computer Science and Applications, 7(1), 535–540

2. Amanpreet, K., & Tarandeep, S. (2010). Segmentation of Continuous Punjabi Speech Signal into Syllables: WCECS’2010 Proceedings. San Francisco.

3. Anwar, M. J., Awais, M. M., Masud, S., & Shamail, S. (2006). Automatic Arabic speech segmentation system. International Journal of Information Technology, 12(6), 102–111.

4. Awais, M. M., Ahmad, W., Masud, S., & Shamail, S. (2006). Continuous Arabic speech segmentation using FFT spectrogram: Innovations in Information Technology Proceedings, Dubai, UAE.

5. Bilmes, J. A. (2003). Buried Markov models: A graphical-modelling approach to automatic speech recognition. Computer Speech and Language, 17(2–3), 213–231.

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