Total: 1
We introduce a new noise suppression method by using a search strategy with multi-model compositions that includes the following models: speech, noise, and their composites. Before noise suppression, a beam search is performed to find the best sequences of these models using noise acoustic models, noise-label n-gram models, and a noise-label lexicon. Noise suppression is frame-synchronously performed by the multiple models selected by the search. We evaluated this method using the E-Nightingale task, which contains voice memoranda spoken by nurses during actual work at hospitals. For this difficult task, the proposed method obtained a 21.6% error reduction rate.