Abstract
With the advent of deep learning there has been a major paradigm shift in how speech signal and text processing techniques work. In this paper, we would like to share our experiences/recent works on applying deep neural networks (DNNs) to adaptive microphone array speech enhancement, sentiment analysis, speech recognition, language recognition and text-to-speech (TTS). In those tasks, many different DNN structures and learning strategies were involved including DNN, convolutional neural network (CNN), recurrent neural network (RNN) and long-short-term memory (LSTM). Experimental results all show DNNs are quite promising.
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