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ICASSP
2010
IEEE

Automatic disfluency removal for improving spoken language translation

13 years 3 months ago
Automatic disfluency removal for improving spoken language translation
Statistical machine translation (SMT) systems for spoken languages suffer from conversational speech phenomena, in particular, the presence of speech dis uencies. We examine the impact of dis uencies from broadcast conversation data on our hierarchical phrasebased SMT system and implement automatic dis uency removal approaches for cleansing the MT input. We evaluate the ef cacy of proposed approaches and investigate the impact of dis uency removal on SMT performance across different dis uency types. We show that for translating Mandarin broadcast conversational transcripts into English, our automatic dis uency removal approaches could produce signi cant improvement in BLEU and TER.
Wen Wang, Gökhan Tür, Jing Zheng, Necip
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where ICASSP
Authors Wen Wang, Gökhan Tür, Jing Zheng, Necip Fazil Ayan
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