Neural network based optimal feature extraction for ASR
نویسندگان
چکیده
The procedure of calculating Mel Frequency based Cepstral Coefficients (MFCC) is shown to resemble a three layer Multilayer Perceptron (MLP) like structure. Such an MLP is employed as a preprocessor in a hybrid HMM-MLP system, and the possibility of optimizing the whole system as a single entity, with respect to a suitable criterion, is pointed out. This system, together with the Maximum Mutual Information (MMI) criterion was tested on a speaker independent, five broad class, isolated phoneme recognition task. Results of these preliminary experiments, which clearly indicate the advantage of optimizable preprocessing, are reported.
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