Discriminative training of language models for text and speech classification
US8306818B2 · kind B2 · utility
12Cited by
9References
10Claims
0Family size
Assignee
Inventors
Key dates
| Filing date | Apr 15, 2008 |
| Grant date | Nov 6, 2012 |
| Priority date | — |
| Expiry date | May 19, 2029 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/183
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods are disclosed for estimating language models such that the conditional likelihood of a class given a word string, which is very well correlated with classification accuracy, is maximized. The methods comprise tuning statistical language model parameters jointly for all classes such that a classifier discriminates between the correct class and the incorrect ones for a given training sentence or utterance. Specific embodiments of the present invention pertain to implementation of the rational function growth transform in the context of a discriminative training technique for n-gram classifiers.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.