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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wei Wu Yun-Cheng Ju Xiao Li Ye-Yi Wang |
| Copyright Year | 2010 |
| Description | Author affiliation: University of Washington, USA (Wei Wu) || Microsoft Research, Washington, U.S.A. (Yun-Cheng Ju; Xiao Li; Ye-Yi Wang) |
| Abstract | Voice search technology has been successfully applied to help drivers reply SMS messages in automobiles, in which a predefined SMS message template set is searched with ASR hypotheses to form the reply candidate list. In order to efficiently organize the SMS message template set and improve the quality of the reply candidate list, we proposed to apply n-gram translation model and logistic regression to detect paraphrase SMS messages. Both of the proposed algorithms outperform the edit distance based paraphrase detection baseline, brining 40.9% and 50.5% EER reduction (relative), respectively. |
| Starting Page | 5326 |
| Ending Page | 5329 |
| File Size | 160954 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424442959 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2010.5494959 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-03-14 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Automobiles Automatic speech recognition Logistics Redundancy Data mining Acoustic signal detection Degradation Support vector machines Design methodology Feature extraction logistic regression SMS message paraphrase detection n-gram translation model |
| Content Type | Text |
| Resource Type | Article |
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