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Nuha-Speech initiative builds Arabic Speech LLMs with 1.5M+ QA samples

Researchers have introduced Nuha-Speech, a project aimed at developing general-purpose Arabic Speech Large Language Models (speech-LLMs). This initiative addresses the underrepresentation of Arabic in multilingual speech-LLMs by creating a large-scale Arabic Speech Question-Answering (SQA) corpus with over 1.5 million training samples. The corpus was used to fine-tune Qwen Omni model variants, and a comprehensive evaluation framework was designed to establish foundational infrastructures for Arabic speech-LLMs despite limited resources. AI

IMPACT This work aims to improve the representation and capabilities of Arabic language models in speech-based AI applications.

RANK_REASON The cluster describes a research paper detailing the creation of a new dataset and the fine-tuning of existing models for a specific language and modality. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Nuha-Speech initiative builds Arabic Speech LLMs with 1.5M+ QA samples

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The cluster describes a research paper detailing the creation of a new dataset and the fine-tuning of existing models for a specific language and modality. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Yingzhi Wang, Reem Alhazzani, Muhammad Alqurishi ·

    Nuha-Speech: Building General-Purpose Arabic Speech-LLMs

    arXiv:2609.11892v1 Announce Type: new Abstract: As Speech Large Language Models (speech-LLMs) become increasingly multilingual, Arabic remains significantly underrepresented, highlighting the need for dedicated infrastructure to train and evaluate Arabic speech-LLMs. To address t…