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English(EN) Measuring the Verifier's Floor: How Much Apparent Rare-Word Text-to-Speech Error Is ASR Error?

研究量化了TTS评估中的ASR错误

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新的研究论文探讨了语音合成（TTS）系统的准确性，通过分析其评估中使用的自动语音识别（ASR）系统引入的错误。研究发现，即使在转录人类语音时，ASR系统也会遗漏相当比例的稀有词，并且这些错误会夸大TTS系统的感知错误率。通过使用多个ASR系统，研究人员能够降低稀有词的表观TTS错误率，尽管这些词仍然是最难处理的。 AI

影响 这项研究强调了在语音合成领域需要更鲁棒的评估指标，这可能导致更准确的TTS系统。

排序理由 该集群包含一篇在arXiv上发表的学术论文，详细介绍了研究结果。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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研究量化了TTS评估中的ASR错误

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该集群包含一篇在arXiv上发表的学术论文，详细介绍了研究结果。[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) · Kirill Borodin, Vasilii Kudryavtsev, Nikita Vasiliev, Grach Mkrtchian ·

    Measuring the Verifier's Floor: How Much Apparent Rare-Word Text-to-Speech Error Is ASR Error?

    arXiv:2610.31470v1 Announce Type: cross Abstract: Text-to-speech (TTS) is usually evaluated by transcribing its output with an automatic speech recognition (ASR) system, so the word error rate also counts recognizer errors. We measure these errors on human recordings of the test …

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