首个多方言阿拉伯语语音任务发布，聚焦方言识别与语音还原。
NADI 2025: The First Multidialectal Arabic Speech Processing Shared Task
- 构建多任务共享评测框架，覆盖方言识别、语音转写与符号恢复。
- 最佳模型在方言识别上达79.8%准确率，语音识别平均WER为35.68。
- 适合语音处理、自然语言处理及中东语言技术研究者参考。
我们介绍了第六届细微阿拉伯语方言识别（NADI 2025）共享任务的成果，该任务聚焦于阿拉伯语语音方言处理，包含三个子任务：口语方言识别（子任务1）、语音识别（子任务2）以及口语方言的标点恢复（子任务3）。共有44支团队注册，测试阶段收到8个独立团队提交的100份有效结果。其中，子任务1有34份提交（来自5个团队），子任务2有47份提交（来自6个团队），子任务3有19份提交（来自2个团队）。最优系统在子任务1中达到79.8%的准确率，在子任务2中整体平均词错误率（WER）为35.68，字符错误率（CER）为12.20；在子任务3中，WER为55，CER为13。这些结果凸显了阿拉伯语方言语音处理的持续挑战，特别是在方言识别、语音识别和标点恢复方面。我们还总结了参赛团队采用的方法，并简要展望了未来NADI赛事的发展方向。
原文摘要 · Abstract (English)
We present the findings of the sixth Nuanced Arabic Dialect Identification (NADI 2025) Shared Task, which focused on Arabic speech dialect processing across three subtasks: spoken dialect identification (Subtask 1), speech recognition (Subtask 2), and diacritic restoration for spoken dialects (Subtask 3). A total of 44 teams registered, and during the testing phase, 100 valid submissions were received from eight unique teams. The distribution was as follows: 34 submissions for Subtask 1 "five teamsæ, 47 submissions for Subtask 2 "six teams", and 19 submissions for Subtask 3 "two teams". The best-performing systems achieved 79.8% accuracy on Subtask 1, 35.68/12.20 WER/CER (overall average) on Subtask 2, and 55/13 WER/CER on Subtask 3. These results highlight the ongoing challenges of Arabic dialect speech processing, particularly in dialect identification, recognition, and diacritic restoration. We also summarize the methods adopted by participating teams and briefly outline directions for future editions of NADI.
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