| Autor: |
Sadeen Alharbi, Muna Alrazgan, Alanoud Alrashed, Turkiayh Alnomasi, Raghad Almojel, Rimah Alharbi, Saja Alharbi, Sahar Alturki, Fatimah Alshehri, Maha Almojil |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
IEEE Access, Vol 9, Pp 131858-131876 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2021.3112535 |
| Popis: |
A huge amount of research has been done in the field of speech signal processing in recent years. In particular, there has been increasing interest in the automatic speech recognition (ASR) technology field. ASR began with simple systems that responded to a limited number of sounds and has evolved into sophisticated systems that respond fluently to natural language. This systematic review of automatic speech recognition is provided to help other researchers with the most significant topics published in the last six years. This research will also help in identifying recent major ASR challenges in real-world environments. In addition, it discusses current research gaps in ASR. This review covers articles available in five research databases that were completed according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol. The search strategy yielded 82 conferences and articles related to the study’s scope for the period 2015–2020. The results presented in this review shed light on research trends in the area of ASR and also suggest new research directions. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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