Arabic dialects speech corpora: a systematic review - Alqadasi, Ammar Mohammed Ali; Zeki, Akram M.; Sunar, Mohd Shahrizal; Hashim, Siti Zaiton Mohd; Salam, Md Sah; Abdulghafor, Rawad (Elsevier, 2025)
Speech processing applications are crucial in various domains, necessitating reliable speech recognition systems built upon suitable speech databases. However, the availability of comprehensive resources for the Arabic language remains limited compared to other languages like English. A systematic review was conducted to identify, analyze, and classify existing Arabic dialect speech databases. Initially, online digital databases and search engines were identified to collect a diverse range of manuscripts for thorough examination. The review encompassed 30 publicly accessible databases and an additional 39 self-databases, which were thoroughly studied, classified based on their characteristics, and subjected to a detailed analysis of research trends. This paper offers a comprehensive discussion on the diverse speech databases developed for various speech processing applications, highlighting the purposes and unique characteristics of Arabic speech databases. By providing valuable insights into their availability, characteristics, challenges, and research directions, this review aims to facilitate researchers' access to suitable resources for their specific applications, encourage the creation of new datasets in underrepresented areas, and promote open and easily accessible databases. Furthermore, the findings contribute to bridging the gap in available Arabic speech databases and serve as a valuable resource for researchers in the field.