Online vocabulary adaptation using contextual information and information retrieval
نویسنده
چکیده
This paper presents an algorithm for automatic online vocabulary adaptation based on contextual information and information retrieval. Experiments are presented on a transcription task of spoken annotations of business cards recorded by a hand-held device. Contextual information is used to trigger web search which is used to adapt the vocabulary for a given business card. Finally, the language model for the adapted vocabulary is modified by taking into account the relative value of each context information source. On the business card task, the proposed algorithm reduces 75% of the out-of-vocabulary rate and 16% of the word error rate.
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