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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Rodriguez, L. Reddy, A. Rose, R. |
| Copyright Year | 2012 |
| Description | Author affiliation: Departamento de Sistemas Informáticos, University of Castilla La Mancha, Spain (Rodriguez, L.) || Dept. of Electrical and Computer Engineering, McGill University, Montreal, Q, Canada (Reddy, A.; Rose, R.) |
| Abstract | This paper is concerned with combining models for decoding an optimum translation for a dictation based machine aided human translation (MAHT) task. Statistical language model (SLM) probabilities in automatic speech recognition (ASR) are updated using statistical machine translation (SMT) model probabilities. The effect of this procedure is evaluated for utterances from human translators dictating translations of source language documents. It is shown that computational complexity is significantly reduced while at the same time word error rate is reduced by 30%. |
| Starting Page | 4949 |
| Ending Page | 4952 |
| File Size | 107207 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467300452 |
| ISSN | 15206149 |
| e-ISBN | 9781467300469 |
| e-ISBN | 9781467300445 |
| DOI | 10.1109/ICASSP.2012.6289030 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-03-25 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Lattices Decoding Speech Humans Computational modeling Probability Vocabulary speech input interfaces speech recognition machine translation |
| Content Type | Text |
| Resource Type | Article |
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