English(EN) Decoder-Side Semantic Conditioning for Low-Bitrate Neural Speech Compression

新的SemDAC方法通过语义条件化提升语音压缩效果

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-10 04:00

研究人员开发了一种新颖的神经语音压缩方法SemDAC，该方法优先考虑语义内容而非波形保真度。通过引入源自HuBERT特征的分层语义条件化，SemDAC在较低比特率下实现了比现有方法显著更高的压缩效率和识别鲁棒性。这种方法将重建引导至关键的语音信息，在各种客观和主观质量指标上优于更高比特率的基线。 AI

影响这项研究可能带来更高效的语音编解码器，从而在低带宽场景下提高音频质量和识别准确性。

排序理由该条目是一篇在arXiv上发表的研究论文，详细介绍了一种新的神经语音压缩方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · Liuyang Bai, Weiyi Lu, Li Guo · 2026-09-10 04:00

用于低比特率神经语音压缩的解码器端语义条件

arXiv:2512.21653v2 Announce Type: replace-cross Abstract: Speech codecs are usually optimized for waveform fidelity, allocating bits to acoustic detail that can be inferred from linguistic structure. This leads to inefficient compression and degraded recognition performance. We p…

本文如何被排名

报道来源 [1]

用于低比特率神经语音压缩的解码器端语义条件

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