Deep learning for environmentally robust speech recognition
Deep learning is an emerging technology that is one of the most promising areas of artificial intelligence. Great strides have been made in recent years which resulted in increased efficiency with regards to many applications, including speech. Despite this, an environmentally Robust Speech Recognit...
| Main Authors: | , , |
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| Format: | Proceeding Paper |
| Language: | English English English |
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AIP Publishing
2020
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/82387/ http://irep.iium.edu.my/82387/13/Certificate%20%20ICEDSA%202020%20%20%2329%20Deep%20Learning%20for%20Environmentally%20Robust%20Speech%20Recognition.pdf http://irep.iium.edu.my/82387/18/82387%20Deep%20learning%20for%20environmentally%20robust%20speech.pdf http://irep.iium.edu.my/82387/24/82387_Deep%20learning%20for%20environmentally%20robust%20speech%20recognition%20SCOPUS.pdf |
| _version_ | 1848789290314629120 |
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| author | Alhamada, A. I. Khalifa, Othman Omran Abdalla, Awad H. |
| author_facet | Alhamada, A. I. Khalifa, Othman Omran Abdalla, Awad H. |
| author_sort | Alhamada, A. I. |
| building | IIUM Repository |
| collection | Online Access |
| description | Deep learning is an emerging technology that is one of the most promising areas of artificial intelligence. Great strides have been made in recent years which resulted in increased efficiency with regards to many applications, including speech. Despite this, an environmentally Robust Speech Recognition system is still far from being achieved. In this article, an investigation of previous work has been conducted. The use of deep learning in speech recognition was analyzed and a proper deep learning architecture was identified. A method using convolutional neural network (CNN) is used with the aim of enhancing the performance of speech recognition systems (SRS). This study found that this CNN-based approach achieves a 94.32% validated accuracy. |
| first_indexed | 2025-11-14T17:54:22Z |
| format | Proceeding Paper |
| id | iium-82387 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English English |
| last_indexed | 2025-11-14T17:54:22Z |
| publishDate | 2020 |
| publisher | AIP Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-823872021-01-20T01:23:20Z http://irep.iium.edu.my/82387/ Deep learning for environmentally robust speech recognition Alhamada, A. I. Khalifa, Othman Omran Abdalla, Awad H. T Technology (General) TD Environmental technology. Sanitary engineering Deep learning is an emerging technology that is one of the most promising areas of artificial intelligence. Great strides have been made in recent years which resulted in increased efficiency with regards to many applications, including speech. Despite this, an environmentally Robust Speech Recognition system is still far from being achieved. In this article, an investigation of previous work has been conducted. The use of deep learning in speech recognition was analyzed and a proper deep learning architecture was identified. A method using convolutional neural network (CNN) is used with the aim of enhancing the performance of speech recognition systems (SRS). This study found that this CNN-based approach achieves a 94.32% validated accuracy. AIP Publishing 2020-12-15 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/82387/13/Certificate%20%20ICEDSA%202020%20%20%2329%20Deep%20Learning%20for%20Environmentally%20Robust%20Speech%20Recognition.pdf application/pdf en http://irep.iium.edu.my/82387/18/82387%20Deep%20learning%20for%20environmentally%20robust%20speech.pdf application/pdf en http://irep.iium.edu.my/82387/24/82387_Deep%20learning%20for%20environmentally%20robust%20speech%20recognition%20SCOPUS.pdf Alhamada, A. I. and Khalifa, Othman Omran and Abdalla, Awad H. (2020) Deep learning for environmentally robust speech recognition. In: 7th International Conference on Electronic Devices, Systems and Applications (ICEDSA2020), 28th - 29th March 2020, Shah Alam, Malaysia. https://aip.scitation.org/doi/10.1063/5.0032382 10.1063/5.0032382 |
| spellingShingle | T Technology (General) TD Environmental technology. Sanitary engineering Alhamada, A. I. Khalifa, Othman Omran Abdalla, Awad H. Deep learning for environmentally robust speech recognition |
| title | Deep learning for environmentally robust speech recognition |
| title_full | Deep learning for environmentally robust speech recognition |
| title_fullStr | Deep learning for environmentally robust speech recognition |
| title_full_unstemmed | Deep learning for environmentally robust speech recognition |
| title_short | Deep learning for environmentally robust speech recognition |
| title_sort | deep learning for environmentally robust speech recognition |
| topic | T Technology (General) TD Environmental technology. Sanitary engineering |
| url | http://irep.iium.edu.my/82387/ http://irep.iium.edu.my/82387/ http://irep.iium.edu.my/82387/ http://irep.iium.edu.my/82387/13/Certificate%20%20ICEDSA%202020%20%20%2329%20Deep%20Learning%20for%20Environmentally%20Robust%20Speech%20Recognition.pdf http://irep.iium.edu.my/82387/18/82387%20Deep%20learning%20for%20environmentally%20robust%20speech.pdf http://irep.iium.edu.my/82387/24/82387_Deep%20learning%20for%20environmentally%20robust%20speech%20recognition%20SCOPUS.pdf |