June 10, 2024, 4:41 a.m. | Abdul Waheed, Karima Kadaoui, Muhammad Abdul-Mageed

cs.CL updates on arXiv.org arxiv.org

arXiv:2406.04512v1 Announce Type: new
Abstract: Arabic is known to present unique challenges for Automatic Speech Recognition (ASR). On one hand, its rich linguistic diversity and wide range of dialects complicate the development of robust, inclusive models. On the other, current multilingual ASR models are compute-intensive and lack proper comprehensive evaluations. In light of these challenges, we distill knowledge from large teacher models into smaller student variants that are more efficient. We also introduce a novel human-annotated dataset covering five under-represented …

arxiv cs.cl cs.sd distillation eess.as knowledge robust robustness type

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