| US 7,478,038 B2 | ||
| Language model adaptation using semantic supervision | ||
| Ciprian Chelba, Seattle, Wash. (US); Milind Mahajan, Redmond, Wash. (US); Alejandro Acero, Bellevue, Wash. (US); and Yik-Cheung Tam, Pittsburgh, Pa. (US) | ||
| Assigned to Microsoft Corporation, Redmond, Wash. (US) | ||
| Filed on Mar. 31, 2004, as Appl. No. 10/814,906. | ||
| Prior Publication US 2005/0228641 A1, Oct. 13, 2005 | ||
| Int. Cl. G06F 17/21 (2006.01) | ||
| U.S. Cl. 704—10 [704/255; 704/9] | 13 Claims |
| 1. A method of adapting an n-gram language model for a new domain, the method comprising:
receiving background data indicative of general text phrases not directed to the new domain;
receiving a set of semantic entities used in the new domain and organized in classes;
generating background n-gram class count data based on the background data and the semantic entities and classes thereof;
receiving adaptation data indicative of text phrases used in the new domain;
generating adaptation n-gram class count data based on the adaptation data and the semantic entities and classes thereof;
training a language model based on the background n-gram class count data and the adaptation n-gram class count data; and
embodying the language model in tangible form.
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