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arXiv · 2605.17846

UrduSpeech: A 156-Hour Urdu Speech Corpus with 12-Dimension Paralinguistic Annotations

Attia Nafees ul Haq·Zeyu Zhu·Jingbin Hu·ChunJiang He·Lei Xie
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Abstract

Despite 230 million speakers, Urdu remains critically under-resourced in speech technology. We introduce UrduSpeech: a large high-fidelity Urdu corpus comprising 156 hours of audio with 12-dimension paralinguistic metadata, encompassing US-Std, US-CS, US-EngPk. To address Right-to-Left script constraints and frequent code-switching, we developed UrduSpeech, a LLM-driven pipeline to curate data across 12 diverse categories, including news, drama, and rare literary forms like Bait-Bazi. We also release a 9-hour US-Benchmark set, manually corrected by native annotators to serve as a standard. Human quality assessment of the primary 156-hour corpus yielded a Mean Opinion Score (MOS) of 4.6 (std = 0.7) with inter-rater reliability confirmed by a 0.68 Cohen's Kappa, validating our curation pipeline's 97.6% confidence score. The corpus maintains a 60-40 gender balance across 71,792 utterances. Our work represents a significant leap toward linguistic inclusivity in global AI. The corpus and code are open-sourced, and a demo page is available.

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Attia Nafees ul Haq, Zeyu Zhu, Jingbin Hu, ChunJiang He, Lei Xie. 2026-05-18. UrduSpeech: A 156-Hour Urdu Speech Corpus with 12-Dimension Paralinguistic Annotations. https://arxiv.org/abs/2605.17846

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