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Impact of automatic comma prediction on pos/name tagging of speech

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8 Author(s)
Hillard, D. ; Electr. Eng. Dept, Univ. of Washington, Seattle, WA ; Huang, Z. ; Ji, H. ; Grishman, R.
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This work looks at the impact of automatically predicted commas on part-of-speech (POS) and name tagging of speech recognition transcripts of Mandarin broadcast news. There is a significant gain in both POS and name tagging accuracy due to using automatically predicted commas over sentence boundary prediction alone. One difference between Mandarin and English is that there are two types of commas, and experiments here show that, while they can be reliably distinguished in automatic prediction, the distinction does not give a clear benefit for POS or name tagging.

Published in:

Spoken Language Technology Workshop, 2006. IEEE

Date of Conference:

10-13 Dec. 2006