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English(EN) Survey of End-to-End Multi-Speaker Automatic Speech Recognition for Monaural Audio

新调查详细介绍了端到端多说话人自动语音识别的进展

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新近发表在arXiv上的调查论文详细介绍了面向单声道音频的端到端（E2E）多说话人自动语音识别（ASR）的进展。该论文系统地回顾了E2E神经方法，按SIMO和SISO等架构范式进行分类，并讨论了在处理长篇语音和说话人归属方面的改进。它还评估了标准基准上的当前方法，并概述了未来更鲁棒的ASR系统的研究方向。 AI

影响 提供了E2E多说话人ASR的结构化概述，指导语音技术未来的研究和开发。

排序理由 该集群包含一篇关于特定AI研究主题的学术调查论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新调查详细介绍了端到端多说话人自动语音识别的进展

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该集群包含一篇关于特定AI研究主题的学术调查论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Xinlu He, Jacob Whitehill ·

    面向单声道音频的端到端多说话人自动语音识别调查

    arXiv:2505.10975v3 Announce Type: replace-cross Abstract: Monaural multi-speaker automatic speech recognition (ASR) remains challenging due to data scarcity and the intrinsic difficulty of recognizing and attributing words to individual speakers, particularly in overlapping speec…

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