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...
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| 主要な著者: | , , |
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| フォーマット: | Conference or Workshop Item |
| 言語: | English English English |
| 出版事項: |
AIP Publishing
2020
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| 主題: | |
| オンライン･アクセス: | 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 http://irep.iium.edu.my/82387/ https://aip.scitation.org/doi/10.1063/5.0032382 |
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| 要約: | 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. |
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