Large list recognition using voice search framework

Large list recognition is usually considered as an automatic speech recognition (ASR) problem. In this paper we propose a method to deal with this problem under the voice search framework. In this framework, the spoken utterance is first converted to text information by a speech recognizer and then the text information is used to search for the final list. We develop an efficient front-end recognizer and propose a back-end three pass post fuzzy retrieval method. The experiment results on the Chinese song name recognition task show that our system gains relative 4.94%, 26.12%, 32.48% error rate reduction for top 1, top 5 and top 10 results respectively upon the conventional grammar constrained recognizer.