Arabic stop consonants characterisation and classification using the normalized energy in frequency bands-Reference-Cited by-同舟云学术

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Arabic stop consonants characterisation and classification using the normalized energy in frequency bands

Published:2017-09-14 Issue:4 Volume:20 Page:869-880
ISSN:1381-2416
Container-title:International Journal of Speech Technology
language:en
Short-container-title:Int J Speech Technol

Author:

Tahiry Karim,Mounir Badia,Mounir Ilham,Elmazouzi Laila,Farchi Abdelmajid

Publisher

Springer Science and Business Media LLC

Subject

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

Link

http://link.springer.com/article/10.1007/s10772-017-9454-9/fulltext.html

Reference31 articles.

1. Abdelatty Ali, A., Spiegel, J. V., & Mueller, P. (2001). Acoustic-phonetic features for the automatic classification of stop consonants. IEEE Transactions on Speech and Audio Processing, 9(8), 833–841.

2. AlDahri, S. S. (2012). A study of voice onset time for modern standard Arabic and classical Arabic. IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC 2012), Hong Kong.

3. AlDahri, S. S., & Alotaibi, Y. A. (2010). A cross language survey of VOT values for stops (/d/, /t/). IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2010), Xiamen, China.

4. Benguerel, A. P., & Bhatia, T. K. (1980). Hindi stop consonants: An acoustic and fiberscopic study. Phonetica, 37, 134–148.

5. Blumstein, S. E., & Stevens, K. N. (1980). Perceptual invariance and onset spectra for stop consonants in different vowel environments. The Journal of the Acoustical Society of America, 67, 648–662.

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Speech Emotion Recognition Using Energies in six bands and Multilayer Perceptron on RAVDESS Dataset;2022 5th International Conference on Advanced Communication Technologies and Networking (CommNet);2022-12-12

2. Arabic Stop Consonant Acoustic Characterization;Advances in Intelligent Systems and Computing;2019

3. Recognition and Classification of Arabic Fricative Consonants;Advances in Intelligent Systems and Computing;2018

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