| 摘要 |
The present invention relates to a method for recognizing speech, which method leads to an improved recognition rate compared to prior art. Within the method a language model is applied which is based on attribute information of a word, which is descriptive for syntactic and/or semantic information and/or the like of the respective word. The method for recognizing speech according to the invention, comprises the steps of receiving (S0) a speech input (SI), generating (S1) a set of ordered hypotheses (OH), wherein each hypothesis contains at least one hypothesis word, generating (S2) attribute information (AI) for at least one of said at least one hypothesis word, the attribute information being generated to be descriptive for syntactic and/or semantic information and/or the like of the respective hypothesis word, using (S3) a language model (LM) which is based on said attribute information (AI) to calculate word probabilities for said at least one of said at least one hypothesis word, which word probabilities are descriptive for the posterior probabilities of the respective hypothesis word given a plurality of previous hypothesis words, using (S4) said word probabilities for generating a set of re-ordered hypotheses (ROH), choosing (S5) at least one best hypothesis (BH) from said set of re-ordered hypotheses (ROH) as a recognition result (RR), and outputting (S6) said recognition result.
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