Investigating modulation spectrogram features for deep neural network-based automatic speech recognition

Abstract

Deep neural network (DNN) based acoustic modelling has been shown to yield significant improvements over Gaussian Mixture Models (GMM) for a variety of automatic speech recognition (ASR) tasks. In addition, it is also becoming popular to use rich speech representations, such as full-resolution spectrograms and perceptually motivated features, as input to… (More)

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