Arabic speech recognition using end‐to‐end deep learning
Abstract Arabic automatic speech recognition (ASR) methods with diacritics have the ability to be integrated with other systems better than Arabic ASR methods without diacritics. In this work, the application of state‐of‐the‐art end‐to‐end deep learning approaches is investigated to build a robust d...
Saved in:
| Main Authors: | Hamzah A. Alsayadi, Abdelaziz A. Abdelhamid, Islam Hegazy, Zaki T. Fayed |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-10-01
|
| Series: | IET Signal Processing |
| Online Access: | https://doi.org/10.1049/sil2.12057 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
End-to-end feature fusion for jointly optimized speech enhancement and automatic speech recognition
by: Mohamed Medani, et al.
Published: (2025-07-01) -
End-to-End Mandarin Speech Reconstruction Based on Ultrasound Tongue Images Using Deep Learning
by: Fengji Li, et al.
Published: (2025-01-01) -
End-to-end handwritten Ge’ez multiple numerals recognition using deep learning
by: Ruchika Malhotra, et al.
Published: (2024-12-01) -
End-to-end neural automatic speech recognition system for low resource languages
by: Sami Dhahbi, et al.
Published: (2025-03-01) -
The analysis of transformer end-to-end model in Real-time interactive scene based on speech recognition technology
by: Ping Li, et al.
Published: (2025-05-01)