A data selection strategy for utterance verification in continuous speech recognition
نویسندگان
چکیده
In this paper, we propose the concept of rival for verifying hypothesis in speech recognition. A likelihood ratio test, based on the rivals model, are investigated for utterance verification in continuous speech recognition. We present a data selection strategy to identity useful subsets of training data to train rival model automatically from training data. And a single pass strategy for utterance verification, namely verification-in-search, is also proposed. Some preliminary experiments on DARPA Communicator travel task have shown the rival models give better verification performance in terms of identifying mis-recognized words from the output of our baseline recognizer.
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