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English(EN) One Mean Log-Mel Vector per Phoneme: Simple and Fast Text Injection for Speech Recognition

新的文本注入方法加速语音识别训练

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种使用非配对文本训练语音识别模型的新方法，与以前的方法相比，训练速度提高了 1.8 倍。这种称为“文本注入”的技术用一个简单的查找表替换了冻结的文本到语音（TTS）模型，该查找表使用每个音素的均值对数梅尔向量。当与外部语言模型结合时，该系统在 LibriSpeech 数据集上达到了最先进的词错误率。研究人员还公开了整个流水线的代码。 AI

影响 这种方法可以实现更快、更高效的语音识别模型训练。

排序理由 该集群包含一篇详细介绍语音识别新方法的学术论文。

在 arXiv cs.AI 阅读 →

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新的文本注入方法加速语音识别训练

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该集群包含一篇详细介绍语音识别新方法的学术论文。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Albert Zeyer, Davyd Naveriani, Dorian Koch, Ralf Schl\"uter, Hermann Ney ·

    每个音素一个均值对数梅尔向量：简单快速的文本注入用于语音识别

    arXiv:2610.34623v1 Announce Type: new Abstract: Text injection trains speech recognition models on unpaired text alongside paired audio. We feed the speech encoder synthetic input derived from text so the whole model learns from it. Previously, we synthesized this input with a fr…

  2. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Hermann Ney ·

    每个音素一个均值对数梅尔向量：简单快速的文本注入语音识别

    Text injection trains speech recognition models on unpaired text alongside paired audio. We feed the speech encoder synthetic input derived from text so the whole model learns from it. Previously, we synthesized this input with a frozen text-to-speech (TTS) model. Here, a simple …

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