A fuzzy decision strategy for topic identification and dynamic selection of language models
نویسندگان
چکیده
A robust strategy for dynamic Language Model (LM) selection, based on topic recognition and switching between topic models, is proposed. It is effective because it relies on a small set of well trained topic−dependent LMs and on reliable topic recognition. By using perplexity as a performance measure of the LM switching model, a tangible reduction is observed with respect to the use of a single, general, static LM.
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عنوان ژورنال:
- Signal Processing
دوره 80 شماره
صفحات -
تاریخ انتشار 2000