An interactive tool for extracting human knowledge in speech recognition

Conventional features for speech recognition have not been evaluated in terms of importance in human speech recognition. In this paper a method for extracting important features in an interactive process has been introduced. This method can be used as an aid for experts in an ASR expert system. It has also been shown, as an application of our method, how an expert might find out the distinguishing features between "m" and "n". As another use, it has been illustrated that how our method could be used to check the sufficiency of information in the quantized filter-bank for speech recognition.

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