基于波形的零延迟无损语音编码

Takenori Yoshimura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, K. Tokuda
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引用次数: 5

摘要

提出了一种基于小波网的高质量语音零延迟无损编码技术。WaveNet生成模型是基于神经网络的语音波形合成的最先进模型,用于编码器和解码器。在编码器中,使用逐样本熵编码对离散语音信号进行无损压缩。该解码器从压缩后的语音信号中完全重建原始语音信号,没有算法延迟。实验结果表明,所提出的编码技术可以以50%的原始比特率传输语音音频波形,并且基于wavenet的语音编码器对未知说话人仍然有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WaveNet-Based Zero-Delay Lossless Speech Coding
This paper presents a WaveNet-based zero-delay lossless speech coding technique for high-quality communications. The WaveNet generative model, which is a state-of-the-art model for neural-network-based speech waveform synthesis, is used in both the encoder and decoder. In the encoder, discrete speech signals are losslessly compressed using sample-by-sample entropy coding. The decoder fully reconstructs the original speech signals from the compressed signals without algorithmic delay. Experimental results show that the proposed coding technique can transmit speech audio waveforms with 50% their original bit rate and the WaveNet-based speech coder remains effective for unknown speakers.
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