| 摘要 |
The invention relates to a method of estimating probabilities of occurrence of speech vocabulary elements in a speech recognition system. By modification of the linguistic speech modeling, further alternatives for reducing the error rate and perplexity of a speech recognition system are proposed. The method according to the invention is characterized in that, in the estimation of a probability of occurrence of a speech vocabulary element, several M-gram probabilities of this element are raised to a higher power by means of an M-gram-specific optimized parameter value, and the powers thus obtained are multiplied by each other, in which the estimation of the probability of occurrence of a speech vocabulary element does not include the case where an M-gram probability with M>1 estimated by means of a first training vocabulary corpus for the speech vocabulary element is multiplied by a quotient raised to a higher power by means of an optimized parameter value, which optimized parameter value is determined by means of the GIS algorithm, and a unigram probability of the element estimated by means of a second training vocabulary corpus serves as a dividend of the quotient, and a unigram probability of the element estimated by means of the first training vocabulary corpus serves as a divisor of the quotient.
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