Combining outputs of multiple LVCSR models by machine learning


This paper proposes to apply machine learning techniques to the task of combining outputs of multiple LVCSR models, where, as features of machine learning, information such as the models which output the hypothesized word, its part-of-speech, and its syllable length are useful for improving the word recognition rate. Experimental results show that the… (More)
DOI: 10.1002/scj.20340


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