Scholarlink

Automatic Speech Recognition (ASR) has gained significant attention in recent years due to its applications in various domains such as voice assistants, transcription services, and language learning. However, developing an ASR system for Arabic poses unique challenges due to the complex phonetics, morphology, dialectal variations, and loss of information during speech production. This paper aims to provide a comprehensive overview of the latest techniques and advancements in Arabic ASR. It covers acoustic modeling techniques, language modeling techniques, challenges and recent solutions, and available datasets for training and evaluation, and evaluation metrics like Word Error Rate (WER), Character Error Rate (CER), and Sentence Error Rate (SER). Overall, this survey paper serves as a comprehensive resource for those seeking a holistic understanding of Arabic speech recognition.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A Review of Speech Recognition and Application to Arabic Speech Recognition

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Eman Aboelela,
  • Omar Mansour

摘要

Automatic Speech Recognition (ASR) has gained significant attention in recent years due to its applications in various domains such as voice assistants, transcription services, and language learning. However, developing an ASR system for Arabic poses unique challenges due to the complex phonetics, morphology, dialectal variations, and loss of information during speech production. This paper aims to provide a comprehensive overview of the latest techniques and advancements in Arabic ASR. It covers acoustic modeling techniques, language modeling techniques, challenges and recent solutions, and available datasets for training and evaluation, and evaluation metrics like Word Error Rate (WER), Character Error Rate (CER), and Sentence Error Rate (SER). Overall, this survey paper serves as a comprehensive resource for those seeking a holistic understanding of Arabic speech recognition.