Adapting machine translation data using damaging channel model
US9697201B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 24, 2014 |
| Grant date | Jul 4, 2017 |
| Priority date | — |
| Expiry date | May 22, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/26
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A speech-to-speech (S2S) translation system may utilize a damaging channel model to adapt machine translation (MT) training data so that a MT engine of the S2S translation system that is trained with the adapted training data can make better use of output received from an automated speech recognition (ASR) engine of the S2S translation system. The S2S translation system may include a MT training module that uses MT technology in order to simulate a particular ASR engine output by treating the ASR engine as a “noisy channel”. A process may include modeling ASR errors of a particular ASR engine based at least in part on output of the ASR engine to create an ASR simulation model, and performing machine translation to generate training data based at least in part on the ASR simulation model. The MT engine of the S2S translation system may then be trained using the generated training data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.