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<p>The ability to recognize and translate human speech has grown in importance. By completing this task, obstacles are removed and smooth communication between people and devices is facilitated. In recent times, researchers have shown a heightened interest in automatic speech recognition (ASR) utilizing artificial intelligence algorithms. These algorithms have yielded superior results in various applications, including speech recognition, making it a highly appealing area of research. However, these impressive outcomes are not consistent for all spoken languages, with Arabic being one of them. The limited availability of suitable datasets hinders the effectiveness of Arabic speech recognition. In this paper, we present an overview of Arabic ASR using neural networks. We survey the state of the art and present several tables for comparison, description, and classification. In addition, this study aims to identify the major challenges in real-world environments. The findings presented in this review shed light on the research trends in the field of Arabic ASR and suggest potential new directions for future research.</p>

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Arabic speech recognition using neural networks: concepts, literature review and challenges

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月11日

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  • Samia Haboussi,
  • Nourredine Oukas,
  • Taha Zerrouki,
  • Halima Djettou

摘要

The ability to recognize and translate human speech has grown in importance. By completing this task, obstacles are removed and smooth communication between people and devices is facilitated. In recent times, researchers have shown a heightened interest in automatic speech recognition (ASR) utilizing artificial intelligence algorithms. These algorithms have yielded superior results in various applications, including speech recognition, making it a highly appealing area of research. However, these impressive outcomes are not consistent for all spoken languages, with Arabic being one of them. The limited availability of suitable datasets hinders the effectiveness of Arabic speech recognition. In this paper, we present an overview of Arabic ASR using neural networks. We survey the state of the art and present several tables for comparison, description, and classification. In addition, this study aims to identify the major challenges in real-world environments. The findings presented in this review shed light on the research trends in the field of Arabic ASR and suggest potential new directions for future research.