A feature extraction system, an automatic speech recognition system, a feature extraction method, an automatic speech recognition method and a method of train

摘要

An automatic speech recognition system, comprising: an input for receiving a speech signal; and a processor configured to: filter an input speech signal using a filter bank comprising a plurality of filters, wherein each filter in the filter bank modifies the input speech signal in the time domain by a different frequency dependent gain, the filter bank outputting a time domain signal from each filter; extract a temporal envelope from the output time domain signal from each filter in the filter bank; frame the temporal envelopes; extract a feature vector for each frame, wherein each feature vector comprises a feature coefficient extracted from the frame of the temporal envelope of the output time domain signal from each filter in the filter bank; input the feature vectors into a deep neural network based classifier, the classifier generating one or more automatic speech recognition hypotheses corresponding to the input speech signal. The filter bank is a Gammatone filter bank. Extracting the temporal envelope from the output time domain signal comprises full wave rectifying the output time domain signal from each filter in the filter bank and low pass filtering each of the rectified signals. A time delay neural network (TDNN) de-noising auto encoder is used.