NDLI: Syllable-based recognition of Arabic & English digits in noisy environment

Content Provider	IEEE Xplore Digital Library
Author	Azmi, M.M. Tolba, H.
Copyright Year	2008
Description	Author affiliation: Dept. of Commun., Alexandria Higher Inst. of Eng., Alexandria (Azmi, M.M.) \|\| Dept. of Commun., Univ. of Alexandria, Alexandria (Tolba, H.)
Abstract	The presence of noise degrades the recognition percent of automatic speech recognition systems. In this paper, we concentrate on the comparison between Arabic and English digits in different conditions of noise using different acoustic units. Speaker-independent hidden Markov models (HMMs)-based speech recognition system was designed using Hidden Markov model toolkit (HTK). The database used of Arabic consists from seventy-five Egyptian speakers. But the database of English is the AURORA Corpus. In Arabic database, experiments show that the recognition rate using syllables outperformed the rate obtained using monophones, triphones and words in different conditions of noise. But in Aurora database, recognition using words or syllables outperforms monophones and triphones. Recognition using words are very close to using syllables because all tidigits of Aurora corpus are monosyllabic Moreover, experiments show that speech recognition using syllables is more robustness to noise than triphones and monophones.
Starting Page	583
Ending Page	586
File Size	122803
Page Count	4
File Format	PDF
ISBN	9781424421787
DOI	10.1109/ICOSP.2008.4697200
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Working environment noise Speech recognition Automatic speech recognition Natural languages Hidden Markov models Databases Acoustic noise Acoustical engineering Error analysis Humans
Content Type	Text
Resource Type	Article

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