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Methods for Encoding and Decoding Audio Signal Using Neural Network Model, and Devices for Performing the Same

机译:使用神经网络模型编码和解码音频信号的方法,以及用于执行相同的设备

摘要

Disclosed are a method for encoding and decoding an audio signal using a neural network model, a training method for a neural network model, and an encoder and decoder for performing the same. According to an embodiment of the present invention, an encoding method includes generating first characteristic information about the input signal using a cyclic encoding model; quantizing the first feature information to output quantized first feature information and a first bitstream; generating a first output signal from the quantized first feature information using a cyclic decoding model; generating second characteristic information for the input signal by using an acyclic encoding model; quantizing the second characteristic information to output quantized second characteristic information and a second bitstream; generating a second output signal from the quantized second feature information using an acyclic decoding model; determining an encoding mode using the input signal, the first and second output signals, and the first and second bitstreams; and outputting the entire bitstream by multiplexing the encoding mode bits with the first or second bitstream selected according to the encoding mode.
机译:公开了一种用于使用神经网络模型,神经网络模型的训练方法和用于执行该的编码器和解码器来编码和解码音频信号的方法。根据本发明的实施例,编码方法包括使用循环编码模型产生关于输入信号的第一特征信息;量化第一特征信息以输出量化的第一特征信息和第一个比特流;使用循环解码模型从量化的第一特征信息生成第一输出信号;通过使用非环路编码模型为输入信号产生第二特征信息;量化第二特征信息以输出量化的第二特征信息和第二比特流;使用无循环解码模型从量化的第二特征信息生成第二输出信号;使用输入信号,第一和第二输出信号和第一和第二比特流确定编码模式;通过使用根据编码模式选择的第一或第二比特流复用编码模式比特来输出整个比特流。

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