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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Maaly, I.A. El-Obaid, M. |
| Copyright Year | 2005 |
| Description | Author affiliation: Fac. of Eng., Khartoum Univ. (Maaly, I.A.) |
| Abstract | As most of the researches on speech recognition (SR) are based on hidden Markov models (HMM), the main theme of this paper is the recognition of Arabic sounds using artificial neural networks. Despite the fact that Arabic is a language that is spoken by millions of people, and it is the sixth (K. Kirchhoff and J. Bilmes, 2002) spoken language in the world, we have faced a scarcity of researches in Arabic language recognition during the preparation of this paper. Speech recognition systems will become more used as they started to replace some of the functions normally accomplished with a keyboard, these and many other reasons encouraged us to continue in this field |
| Starting Page | 1246 |
| Ending Page | 1247 |
| File Size | 1167466 |
| Page Count | 2 |
| File Format | |
| ISBN | 0780395212 |
| DOI | 10.1109/ICTTA.2006.1684556 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-04-24 |
| Publisher Place | Syria |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Speech Recognition Speech analysis Natural languages Artificial neural networks Neural Networks Linear predictive coding Arabic Phonemes Cepstral analysis Databases Signal processing algorithms Hidden Markov models Speech recognition Finite impulse response filter |
| Content Type | Text |
| Resource Type | Article |
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