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Speech recognition with sequence-to-sequence models

机译:用序列到序列模型的语音识别

摘要

Methods, systems, and apparatus, including computer-readable media, for performing speech recognition using sequence-to-sequence models. An automated speech recognition (ASR) system receives audio data for an utterance and provides features indicative of acoustic characteristics of the utterance as input to an encoder. The system processes an output of the encoder using an attender to generate a context vector and generates speech recognition scores using the context vector and a decoder trained using a training process that selects at least one input to the decoder with a predetermined probability. An input to the decoder during training is selected between input data based on a known value for an element in a training example, and input data based on an output of the decoder for the element in the training example. A transcription is generated for the utterance using word elements selected based on the speech recognition scores. The transcription is provided as an output of the ASR system.
机译:方法,系统和设备,包括计算机可读介质,用于使用序列到序列模型执行语音识别。自动语音识别(ASR)系统接收发话机的音频数据,并提供指示对编码器的输入的声学的声学特性的特征。系统使用参与者处理编码器的输出以生成上下文向量,并使用上下文向量生成语音识别分数,并使用使用预定概率选择至少一个输入到解码器的训练过程的解码器。在训练期间基于训练示例中的元素的已知值在输入数据之间选择对解码器的输入,以及基于训练示例中的元素的解码器的输出输入数据。使用基于语音识别分数选择的字元素来生成转录。转录作为ASR系统的输出提供。

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