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Variable-component deep neural network for robust speech recognition

机译:可变分量深度神经网络用于鲁棒语音识别

摘要

Systems and methods for speech recognition incorporating environmental variables are provided. The systems and methods capture speech to be recognized. The speech is then recognized utilizing a variable component deep neural network (DNN). The variable component DNN processes the captured speech by incorporating an environment variable. The environment variable may be any variable that is dependent on environmental conditions or the relation of the user, the client device, and the environment. For example, the environment variable may be based on noise of the environment and represented as a signal-to-noise ratio. The variable component DNN may incorporate the environment variable in different ways. For instance, the environment variable may be incorporated into weighting matrices and biases of the DNN, the outputs of the hidden layers of the DNN, or the activation functions of the nodes of the DNN.
机译:提供了结合了环境变量的用于语音识别的系统和方法。该系统和方法捕获要识别的语音。然后利用可变成分深度神经网络(DNN)识别语音。变量组件DNN通过合并环境变量来处理捕获的语音。环境变量可以是取决于环境条件或用户,客户端设备和环境的关系的任何变量。例如,环境变量可以基于环境的噪声并且被表示为信噪比。变量组件DNN可以以不同方式合并环境变量。例如,可以将环境变量并入DNN的加权矩阵和偏差,DNN的隐藏层的输出或DNN的节点的激活函数中。

著录项

  • 公开/公告号US10019990B2

    专利类型

  • 公开/公告日2018-07-10

    原文格式PDF

  • 申请/专利权人 MICROSOFT TECHNOLOGY LICENSING LLC;

    申请/专利号US201414414621

  • 发明设计人 JINYU LI;RUI ZHAO;YIFAN GONG;

    申请日2014-09-09

  • 分类号G10L15/20;G10L15/16;G10L19/24;G10L25/84;

  • 国家 US

  • 入库时间 2022-08-21 13:03:29

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