发明授权
- 专利标题: Discriminative training of language models for text and speech classification
- 专利标题(中): 文本和语言分类语言模型的歧视性训练
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申请号: US12103035申请日: 2008-04-15
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公开(公告)号: US08306818B2公开(公告)日: 2012-11-06
- 发明人: Ciprian Chelba , Alejandro Acero , Milind Mahajan
- 申请人: Ciprian Chelba , Alejandro Acero , Milind Mahajan
- 申请人地址: US WA Redmond
- 专利权人: Microsoft Corporation
- 当前专利权人: Microsoft Corporation
- 当前专利权人地址: US WA Redmond
- 代理机构: Westman, Champlin & Kelly, P.A.
- 主分类号: G10L15/00
- IPC分类号: G10L15/00 ; G06F17/27
摘要:
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.
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