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English(EN) Interleaved Speech Language Models Latently Work In Text

研究发现:语音语言模型会隐式转录口语

一篇新发表在arXiv上的研究论文探讨了交织式语音语言模型(SLMs)的内部工作机制。研究表明,即使这些模型没有经过显式的语音识别训练,也会经历一个隐式的转录阶段。在此阶段,中间层可以解码口语的文本表示,转录文本在相当一部分数据中作为首选候选。随后,模型在文本域中预测下一个词,之后可能返回到语音域,这揭示了SLMs内部语音和文本模态的交互方式,并可能指导未来的优化。 AI

影响 深入了解语音语言模型的内部机制,可能指导未来的优化。

排序理由 发表在arXiv上的研究论文,详细介绍了语音语言模型的内部机制。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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研究发现:语音语言模型会隐式转录口语

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发表在arXiv上的研究论文,详细介绍了语音语言模型的内部机制。[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) · Yossi Adi ·

    交错语音语言模型在文本中潜在工作

    Speech language models (SLMs) have been extensively studied, with the common paradigm incorporating text data and pre-trained text LMs. A leading approach is speech-text interleaving in which models are trained over sequences containing both speech and text tokens, aiming to boos…