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Outline

Title
Abstract
Introduction
Related Works A. Previous Arabic Asr
Machine Learning Methods for Arabic Asr
Deep Learning Methods for Arabic Asr
Audio Data Collection
Data Cleaning and Annotation
Ref Summary Alghmadi et al. [77]
Future Research Direction on Arabic Asr
Conclusions
References
All Topics
Computer Science

Arabic Speech Recognition: Advancement and Challenges

Profile image of haifa Alhassonhaifa Alhasson

2024, IEEE access

https://doi.org/10.1109/ACCESS.2024.3376237
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29 pages

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Abstract

Speech recognition is a captivating process that revolutionizes human-computer interactions, allowing us to interact and control machines through spoken commands. The foundation of speech recognition lies in understanding a given language's linguistic and textual characteristics. Although automatic speech recognition (ASR) systems flawlessly convert speech into text for various international languages, their implementation for Arabic remains inadequate. In this research, we diligently explore the current state of Arabic ASR systems and unveil the challenges encountered during their development. We categorize these challenges into two groups: those specific to the Arabic language and those that are more general. Additionally, we propose strategies to overcome these obstacles and emphasize the need for ASR architectures tailored to the Arabic language's unique grammatical and phonetic structure. In addition, we provide a comprehensive and explicit description of various feature extraction methods, language models, and acoustic models utilized in the Arabic ASR system.

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