| Autor: |
Ashifur Rahman, Md. Mohsin Kabir, M. F. Mridha, Mohammed Alatiyyah, Haifa F. Alhasson, Shuaa S. Alharbi |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 12, Pp 39689-39716 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3376237 |
| Popis: |
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 more general. 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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