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English(EN) Few-Shot Contrastive Adaptation for Audio Abuse Detection in Low-Resource Indic Languages

CLAP模型赋能低资源印度语言的音频滥用检测

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种利用CLAP模型检测低资源印度语言中音频滥用的方法。该方法绕过了对准确语音转文本转录的需求，而这种转录对于这些语言通常是不可靠的。通过使用CLAP现有的音频表示和轻量级分类器，即使每种语言的标记数据很少，该系统也能达到接近完全监督方法的性能。这表明CLAP作为跨语言音频滥用检测的成本效益基础的潜力。 AI

影响 降低了资源匮乏语言中音频滥用检测的门槛，可能提高在线安全性。

排序理由 研究论文，详细介绍了音频滥用检测的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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CLAP模型赋能低资源印度语言的音频滥用检测

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研究论文，详细介绍了音频滥用检测的新方法。[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) · Aditya Narayan Sankaran, Reza Farahbakhsh, Noel Crespi ·

    低资源印度语言音频滥用检测的少样本对比适应

    arXiv:2604.09094v2 Announce Type: replace-cross Abstract: Abusive and hateful speech is increasingly spoken rather than written, surfacing in voice notes, calls, and short-form videos. Most detection systems still transcribe speech to text before classifying it, but transcription…

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