Papers by Bashar Talafha

2 papers
Zero-Shot Context-Aware ASR for Diverse Arabic Varieties (2026.findings-acl)

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Challenge: Large-scale multilingual ASR has substantially improved recognition for high-resource languages.
Approach: They propose a proxy-guided -best selection paradigm that conditions inference on external side information without parameter updates.
Outcome: The proposed model reduces WER by 15.6% relative and recovers a fraction of oracle n-best gains on the common voice MSA testbed.
Casablanca: Data and Models for Multidialectal Arabic Speech Recognition (2024.emnlp-main)

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Challenge: despite recent advances in speech processing, the majority of world languages and dialects remain uncovered.
Approach: They propose to collect and transcribe a new Arabic dataset for eight dialects . they also develop strong baselines exploiting the new dataset .
Outcome: The proposed dataset covers eight Arabic dialects, including Algerian, Egyptian, Emirati, Jordanian, Mauritanian, Moroccan, Palestinian, and Yemeni.

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