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English(EN) Benchmarking Language Modeling for Lossless Compression of Full-Fidelity Audio

语言模型通过新的分词实现音频无损压缩

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种名为 Trilobyte 的新字节级分词方案，供语言模型实现全保真音频的无损压缩。该方法解决了音频更高比特深度带来的词汇量扩展问题，能够对 16 位和 24 位音频进行实际压缩。虽然该方法在 8 位和 16 位音频压缩方面表现出最先进的性能，优于 FLAC 等现有编解码器，但随着比特深度超过 8 位，性能提升变得不那么显著。 AI

影响 这项研究展示了语言模型在音频压缩方面的新颖应用，有望提高高保真音频存储和传输的效率。

排序理由 该集群包含一篇学术论文，详细介绍了使用语言模型进行音频压缩的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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语言模型通过新的分词实现音频无损压缩

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该集群包含一篇学术论文，详细介绍了使用语言模型进行音频压缩的新方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Phillip Long, Zachary Novack, Chris Donahue ·

    语言模型在全保真音频无损压缩上的基准测试

    arXiv:2603.08683v2 Announce Type: replace-cross Abstract: Autoregressive "language" models (LMs) trained on raw waveforms can be repurposed for lossless audio compression, but prior work is limited to 8-bit audio, leaving open whether such approaches work for practical settings (…

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