Deep Investigation of the Recent Advances in Dialectal Arabic Speech Recognition
Hamzah A Alsayadi, Islam Hegazy, Fayed, Zaki T., Alotaibi, Bandar, Abdelhamid, Abdelaziz,
Speech recognition systems play an important role in human–machine interactions. Many systems exist for Arabic speech, however, there are limited systems for dialectal Arabic speech. The Arabic language comprises many properties, some of which are ideal for building automatic speech recognition systems such as syntax and phonology, while other properties are unsuitable for developing speech systems. Importantly, most data are in non-diacritized form, vary in dialect, and contain morphological complexity. Moreover, the Arabic dialects lack a standard structure. In this paper, we present an overview and summation of dialectal Arabic speech recognition systems using different approaches and techniques. The main goal of this paper is to compare and discuss different studies in dialectal Arabic speech systems including several criteria such as techniques, datasets, evaluation metrics, and dialect types. The study also includes a description of some techniques used in all steps of the dialectal Arabic speech system and introduces challenges and problems. Overall, more studies are required to obtain a more accurate speech system for dialectal Arabic.
|Title||Deep Investigation of the Recent Advances in Dialectal Arabic Speech Recognition||Authors||Hamzah A Alsayadi ; Islam Hegazy ; Fayed, Zaki T. ; Alotaibi, Bandar; Abdelhamid, Abdelaziz||Keywords||Speech recognition;Dialect Arabic;Dialectal Arabic ASR;Acoustic modeling||Issue Date||23-May-2022||Publisher||IEEE||Journal||IEEE Access||ISSN||2169-3536||DOI||10.1109/ACCESS.2022.3177191||Scopus ID||2-s2.0-85130774678|
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