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English(EN) AVCC: Audio-Visual Conversation Corpus for Turn-Taking Prediction with a Human Benchmark

新的AVCC语料库旨在预测对话AI的轮次转换

研究人员推出了视听对话语料库(AVCC),这是一个旨在改进对话轮次转换预测的新数据集。该语料库涵盖了31小时的两人和三人在线讨论的音频和视频,旨在与单摄像头和麦克风设置一起使用,模仿对话代理和社交机器人的能力。AVCC包含一个基准测试,其中包含说话人分离的测试分区、单词级别的文本记录以及人类参考基准测试,用于评估模型在预测下一位说话者方面的性能与人类能力相比。 AI

影响 这个新语料库可以通过提高对话AI代理预测和管理轮次转换的能力,来推动更自然、更高效的对话AI代理的发展。

排序理由 发布用于特定NLP任务的新学术语料库和基准测试。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的AVCC语料库旨在预测对话AI的轮次转换

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发布用于特定NLP任务的新学术语料库和基准测试。[lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Haotian Qi, Gabriel Skantze ·

    AVCC:用于带有人类基准的轮次预测的音频-视觉对话语料库

    arXiv:2611.13957v1 Announce Type: new Abstract: } Predicting who will speak next, and when, is a prerequisite for conversational agents and social robots that take turns without waiting for silence. Multiparty next-speaker prediction (NSP) has been studied on corpora with per-spe…