TY - GEN
T1 - Improving the arabic pronunciation dictionary for phone and word recognition with linguistically-based pronunciation rules
AU - Biadsy, Fadi
AU - Habash, Nizar
AU - Hirschberg, Julia
PY - 2009
Y1 - 2009
N2 - In this paper, we show that linguistically motivated pronunciation rules can improve phone and word recognition results for Modern Standard Arabic (MSA). Using these rules and the MADA morphological analysis and disambiguation tool, multiple pronunciations per word are automatically generated to build two pronunciation dictionaries; one for training and another for decoding. We demonstrate that the use of these rules can significantly improve both MSA phone recognition and MSA word recognition accuracies over a baseline system using pronunciation rules typically employed in previous work on MSA Automatic Speech Recognition (ASR). We obtain a significant improvement in absolute accuracy in phone recognition of 3.77%-7.29% and a significant improvement of 4.1% in absolute accuracy in ASR.
AB - In this paper, we show that linguistically motivated pronunciation rules can improve phone and word recognition results for Modern Standard Arabic (MSA). Using these rules and the MADA morphological analysis and disambiguation tool, multiple pronunciations per word are automatically generated to build two pronunciation dictionaries; one for training and another for decoding. We demonstrate that the use of these rules can significantly improve both MSA phone recognition and MSA word recognition accuracies over a baseline system using pronunciation rules typically employed in previous work on MSA Automatic Speech Recognition (ASR). We obtain a significant improvement in absolute accuracy in phone recognition of 3.77%-7.29% and a significant improvement of 4.1% in absolute accuracy in ASR.
UR - http://www.scopus.com/inward/record.url?scp=80052968837&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80052968837&partnerID=8YFLogxK
U2 - 10.3115/1620754.1620812
DO - 10.3115/1620754.1620812
M3 - Conference contribution
AN - SCOPUS:80052968837
SN - 9781932432411
T3 - NAACL HLT 2009 - Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Proceedings of the Conference
SP - 397
EP - 405
BT - NAACL HLT 2009 - Human Language Technologies
PB - Association for Computational Linguistics (ACL)
T2 - Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, NAACL HLT 2009
Y2 - 31 May 2009 through 5 June 2009
ER -