Sequence classification for machine translation
US7783473B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 28, 2006 |
| Grant date | Aug 24, 2010 |
| Priority date | — |
| Expiry date | May 8, 2029 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F40/44
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Classification of sequences, such as the translation of natural language sentences, is carried out using an independence assumption. The independence assumption is an assumption that the probability of a correct translation of a source sentence word into a particular target sentence word is independent of the translation of other words in the sentence. Although this assumption is not a correct one, a high level of word translation accuracy is nonetheless achieved. In particular, discriminative training is used to develop models for each target vocabulary word based on a set of features of the corresponding source word in training sentences, with at least one of those features relating to the context of the source word. Each model comprises a weight vector for the corresponding target vocabulary word. The weights comprising the vectors are associated with respective ones of the features; each weight is a measure of the extent to which the presence of that feature for the source word makes it more probable that the target word in question is the correct one.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.