Improved morphological decomposition for Arabic broadcast news transcription
Author(s)
Ng, Tim; Nguyen, Kham; Zbib, Rabih M.; Nguyen, Long
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In this paper, we show the progress for Arabic speech recognition by incorporating contextual information into the process of morphological decomposition. The new approach achieves lower out-of-vocabulary and word error rates when compared to our previous work, in which the morphological decomposition relies on word-level information only. We also describe how the vocalization procedure is improved to produce pronunciations for some dialect Arabic words. By using the new approach, we reduced the word error by 0.8% absolute (4.7% relative) when compared to the baseline approach.
Date issued
2009-05Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering; Massachusetts Institute of Technology. Computer Science and Artificial Intelligence LaboratoryJournal
IEEE International Conference on Acoustics, Speech and Signal Processing, 2009. ICASSP 2009.
Publisher
Institute of Electrical and Electronics Engineers
Citation
Tim Ng et al. “Improved morphological decomposition for Arabic broadcast news transcription.” Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on. 2009. 4309-4312. © Copyright 2009 IEEE
Version: Final published version
Other identifiers
INSPEC Accession Number: 10700940
ISBN
978-1-4244-2353-8
ISSN
1520-6149