Sciweavers

Share
TASLP
2008

Joint Morphological-Lexical Language Modeling for Processing Morphologically Rich Languages With Application to Dialectal Arabic

9 years 11 months ago
Joint Morphological-Lexical Language Modeling for Processing Morphologically Rich Languages With Application to Dialectal Arabic
Language modeling for an inflected language such as Arabic poses new challenges for speech recognition and machine translation due to its rich morphology. Rich morphology results in large increases in out-of-vocabulary (OOV) rate and poor language model parameter estimation in the absence of large quantities of data. In this study, we present a joint morphological-lexical language model (JMLLM) that takes advantage of Arabic morphology. JMLLM combines morphological segments with the underlying lexical items and additional available information sources with regards to morphological segments and lexical items in a single joint model. Joint representation and modeling of morphological and lexical items reduces the OOV rate and provides smooth probability estimates while keeping the predictive power of whole words. Speech recognition and machine translation experiments in dialectal-Arabic show improvements over word and morpheme based trigram language models. We also show that as the tight...
Ruhi Sarikaya, Mohamed Afify, Yonggang Deng, Hakan
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where TASLP
Authors Ruhi Sarikaya, Mohamed Afify, Yonggang Deng, Hakan Erdogan, Yuqing Gao
Comments (0)
books