Obaid Ullah Ahmad

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About

Obaid Ullah Ahmad is a pioneering researcher in speech emotion recognition, with a particular focus on the Urdu language—a domain that has historically lacked sufficient resources. His work addresses a critical gap in affective computing, where most datasets and models are limited to languages like English, German, and Italian. Ahmad’s most cited paper, "Speech emotion recognition for the Urdu language" (2022, 16 citations), establishes foundational methods for identifying emotional states from Urdu speech signals, demonstrating the feasibility of cross-linguistic emotion analysis. His earlier contribution, "SEMOUR: A Scripted Emotional Speech Repository for Urdu" (2021, 11 citations), introduced the first scripted emotional speech dataset for Urdu, providing a vital resource for training reliable speech emotion recognition systems. By creating SEMOUR, Ahmad enabled researchers to develop and benchmark models in a language spoken by over 230 million people worldwide. His work has significant implications for human-computer interaction, mental health monitoring, and culturally inclusive AI. Ahmad’s contributions are particularly notable for their emphasis on data scarcity and linguistic diversity, positioning him as a key figure in expanding emotion recognition technology to underrepresented languages.