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RESOLVING TIME-DELAYS USING GENERATIVE MODELS

机译:使用生成模型解决时间延迟

摘要

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating audio output samples predicted to be communicated by a user. One example system includes a first user device having a first user. The first user device initiates a communication session between the first user and a second user of a second user device. The first user device obtains a neural network model of the second user. The neural network model is trained to generate, conditioned on audio input samples received up to a current time step, an audio output sample predicted to be communicated by the second user at a next time step. The user device repeatedly provides received audio input samples as input to the neural network model and plays audio output samples generated by the neural network model in place of received audio input samples communicated by the second user.
机译:方法,系统和装置,包括在计算机存储介质上编码的计算机程序,用于生成预测要由用户传达的音频输出样本。一个示例系统包括具有第一用户的第一用户设备。第一用户设备发起第一用户和第二用户设备的第二用户之间的通信会话。第一用户设备获得第二用户的神经网络模型。训练神经网络模型,以直到当前时间步长之前接收到的音频输入样本为条件,生成预测在第二时间步长下由第二用户传达的音频输出样本。用户设备重复地将接收到的音频输入样本作为输入提供给神经网络模型,并播放由神经网络模型生成的音频输出样本,以代替第二用户传达的接收到的音频输入样本。

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