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English(EN) Ruby-OPD: Enhancing Pronunciation Controllability and Accuracy for Flow-Matching Text-to-Speech via On-Policy Distillation

新的 TTS 框架提高了日语发音的准确性和可控性

研究人员开发了 Ruby-OPD,这是一个新颖的两阶段框架,旨在提高日语文本到语音(TTS)系统中发音的准确性和可控性。该框架解决了日语非分段特性带来的挑战,日语混合了汉字和假名,并具有广泛的同音异义词。该系统利用带有拼写扰动的 Ruby 文本表示来保持表面形式和目标发音,并在仅文本语料库上使用 On-Policy Distillation (OPD) 来提高发音准确性,而无需配对语音数据。在 Joyo-Kanji-Yomi 基准测试中,Ruby-OPD 达到了 97.13% 的准确率,展示了强大的可控性和改进的发音。 AI

影响 提高了具有复杂拼写和发音的语言的 TTS 能力。

排序理由 详细介绍一种新的文本到语音方法的学术论文。[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 →

新的 TTS 框架提高了日语发音的准确性和可控性

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详细介绍一种新的文本到语音方法的学术论文。[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) · Rui Hu, Xiaolong Lin, Zhenpeng Zhan ·

    Ruby-OPD:通过 On-Policy Distillation 增强流匹配文本到语音的读音可控性和准确性

    arXiv:2611.06403v1 Announce Type: new Abstract: Achieving both high pronunciation accuracy and fine-grained controllability remains a central challenge in Japanese text-to-speech (TTS), as Japanese is an unsegmented language mixing logographic Kanji and phonographic Kana with ext…