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English(EN) DLLM-TTS: Block Discrete Diffusion Language Model for Text-to-Speech Synthesis

DLLM-TTS框架实现更快、更准确的文本到语音合成

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出了一种新颖的文本到语音合成框架DLLM-TTS，该框架解决了语音可懂度和生成速度之间的权衡问题。这种新方法将TTS表述为在X-Codec2神经音频编解码器令牌上的条件块状离散扩散。通过将序列分解为块并在每个块内应用掩码扩散，DLLM-TTS实现了高效的并行生成，实时因子为0.15，同时在Seed-TTS-eval等基准测试中保持了有竞争力的性能。 AI

影响 该框架为更高效、更节省数据的语音合成提供了一条潜在途径，提高了实时生成能力。

排序理由 该集群描述了一篇关于文本到语音合成新框架的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

DLLM-TTS框架实现更快、更准确的文本到语音合成

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该集群描述了一篇关于文本到语音合成新框架的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Wasim Madha, Nityanand Mathur, Hamees Sayed, Apoorv Singh, Sameer Khurana, Akshat Mandloi, Sudarshan Kamath ·

    DLLM-TTS：用于文本到语音合成的块离散扩散语言模型

    arXiv:2608.00011v1 Announce Type: new Abstract: Current text-to-speech systems face a trade-off: autoregres- sive codec language models produce highly intelligible speech but require large-scale models and training data and decode tokens sequentially, while non-autoregressive app…

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