A Hybrid Semantic and Word Based Language Model and Its Applications
Jun Hou · Zhongwen xinxi xuebao · 2001
A hybrid semantic and word based language model is brought forward in this paper.The performance of the model is tested in semantic tagging and Mandarin speech recognition,and compared with traditional N gram and semantic language models.The hybrid model better describes the relation between semantics and words and achieves a lower perplexity in tagging corpus.In Mandarin speech recognition,this model shows a better performance and requires less memory space than the word based trigram model.