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STATISTICAL-ANALYSIS-BASED RESET OF RECURRENT NEURAL NETWORKS FOR AUTOMATIC SPEECH RECOGNITION
STATISTICAL-ANALYSIS-BASED RESET OF RECURRENT NEURAL NETWORKS FOR AUTOMATIC SPEECH RECOGNITION
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机译:基于统计分析的递归神经网络对语音自动识别的重置
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摘要
Techniques are provided for calculating reset parameters for recurrent neural networks (RNN). A methodology implementing the techniques according to an embodiment includes generating a sequence of statistics. The calculation of each statistic is based on outputs of an RNN that is periodically re-initialized at a selected RNN reset time such that each of the calculated statistics is associated with a unique RNN reset time selected from a pre-determined range of reset times. The method further includes analyzing the sequence to identify a maximum interval during which the sequence remains relatively constant. The method further includes selecting a reset time parameter and reset context duration parameter, for re-initialization of the RNN during operation. The reset time parameter is based on the duration of the identified maximum interval and the reset context duration parameter is based on a time associated with the starting point of the identified maximum interval.
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