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    • 8. 发明申请
    • SPEAKER RECOGNITION USING NEURAL NETWORKS
    • 使用神经网络的扬声器识别
    • US20160293167A1
    • 2016-10-06
    • US15179717
    • 2016-06-10
    • Google Inc.
    • Yu-hsin Joyce ChenIgnacio Lopez MorenoTara N. SainathMaria Carolina Parada San Martin
    • G10L17/18G10L17/22G10L17/08
    • G10L17/18G06N3/0454G10L17/08G10L17/22H04N21/23406H04N21/23476Y10S707/99953
    • Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing speaker verification. In one aspect, a method includes accessing a neural network having an input layer that provides inputs to a first hidden layer whose nodes are respectively connected to only a proper subset of the inputs from the input layer. Speech data that corresponds to a particular utterance may be provided as input to the input layer of the neural network. A representation of activations that occur in response to the speech data at a particular layer of the neural network that was configured as a hidden layer during training of the neural network may be generated. A determination of whether the particular utterance was likely spoken by a particular speaker may be made based at least on the generated representation. An indication of whether the particular utterance was likely spoken by the particular speaker may be provided.
    • 方法,系统和装置,包括在计算机存储介质上编码的用于执行说话者验证的计算机程序。 一方面,一种方法包括访问具有输入层的神经网络,所述输入层向第一隐藏层提供输入,所述第一隐藏层的节点仅分别连接到来自输入层的输入的适当子集。 可以将对应于特定话语的语音数据提供给神经网络的输入层的输入。 可以生成在神经网络的训练期间被配置为隐藏层的神经网络的特定层响应于语音数据而发生的激活的表示。 可以至少基于所生成的表示来确定特定说话者是否可能说出特定话语的确定。 可以提供特定说话者是否可能说出特定话语的指示。