English(EN) WASIL: In-the-Wild Arabic Spoken Interactions with LLMs

新数据集WASIL增强了阿拉伯语大型语言模型口语交互能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-01 04:00

研究人员推出了WASIL，一个旨在改善阿拉伯语口语与大型语言模型（LLMs）交互的新数据集。该数据集包含超过8,500轮真实场景下的口语交互，附带音频、自动语音识别（ASR）假设、助手响应和用户反馈，其中14.2%的交互被标记为不满意。WASIL还包含一个2,000轮的测试集，涵盖现代标准阿拉伯语和四种主要方言，并附有可回答性标注，以区分ASR错误和真正的无法回答。该资源旨在通过区分语音识别问题和模型固有的能力，来促进对LLM语音助手的更好评估。 AI

影响能够更准确地评估和开发阿拉伯语AI助手。

排序理由该条目是一篇研究论文，详细介绍了用于阿拉伯语口语与LLM交互的新数据集。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Zien Sheikh Ali, Hamdy Mubarak, Soon-Gyo Jung, Hunzalah Hassan Bhatti, Firoj Alam, Shammur Absar Chowdhury · 2026-10-01 04:00

WASIL：LLM的野外阿拉伯语口语交互

arXiv:2605.16364v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) voice assistants are commonly built as cascaded Automatic Speech recognition (ASR) to LLM systems, where recognition errors can distort user intent. Dislikes may also arise from ambiguous, out-…

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WASIL：LLM的野外阿拉伯语口语交互

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