136 / 2017-09-14 10:52:57
Isolated Word Recognition using LSTM network
LSTM, mel-spectrogram,classification, isolated word recognition
全文待审
维军 张 / 上海交通大学
This Paper aims to presents an approach of ASR system based on isolated word structure using mel-spectrogram feature and recurrent neural network model. The mel-spectrogram feature used to capture the significant characteristics of the speech signals. A Long Short Term Memory (LSTM) architecture for variable length feature sequence classification is presented. However, it can be applied to any sequence modelling or classification task. The experimental setup includes words of Chinese language collected from five speakers. These words were spoken in an acoustically balanced, noise free environment.The experimental results show about 16.44% improvement when compared with Dynamic Time Wrapping (DTW) based method.
重要日期
  • 会议日期

    12月15日

    2017

    12月17日

    2017

  • 09月10日 2017

    初稿截稿日期

  • 09月20日 2017

    初稿录用通知日期

  • 09月30日 2017

    终稿截稿日期

  • 12月17日 2017

    注册截止日期

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