An English Teaching Pronunciation Detection and Recognition Algorithm Based on Cluster Analysis and Improved SSD
The accuracy of English pronunciation is the key index to evaluate the quality of English teaching. Correct pronunciation and smooth language flow are the expectations of every student for English learning. Aiming at the poor effect and slow speed of the original SSD (Single Shot MultiBox Detector)...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/1626229 |
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| _version_ | 1832554960850518016 |
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| author | Dongxiao Peng |
| author_facet | Dongxiao Peng |
| author_sort | Dongxiao Peng |
| collection | DOAJ |
| description | The accuracy of English pronunciation is the key index to evaluate the quality of English teaching. Correct pronunciation and smooth language flow are the expectations of every student for English learning. Aiming at the poor effect and slow speed of the original SSD (Single Shot MultiBox Detector) algorithm in English teaching pronunciation detection, this paper proposes a clustering and improved SSD algorithm for English teaching pronunciation detection and recognition. The algorithm improves the concept module to enhance the feature extraction ability of the network and improve the detection speed. Meanwhile, it integrates multiscale features to realize multilayer multiplexing and equalization of features, so as to improve the detection effect of small target sound. This algorithm extracts more features by introducing channel attention mechanism, which increases the detection accuracy while reducing computation. In order to optimize the network’s ability to extract target location information, K-means clustering method is used to set the default parameters that are more in line with the characteristics of target samples. The experimental results showed that the proposed algorithm can accurately evaluate the pronunciation quality of reading aloud, so as to effectively reflect the oral English level of the reader. |
| format | Article |
| id | doaj-art-541381836eb4444483074e46f59b2362 |
| institution | Kabale University |
| issn | 2090-0155 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-541381836eb4444483074e46f59b23622025-02-03T05:49:59ZengWileyJournal of Electrical and Computer Engineering2090-01552022-01-01202210.1155/2022/1626229An English Teaching Pronunciation Detection and Recognition Algorithm Based on Cluster Analysis and Improved SSDDongxiao Peng0Foreign Language SchoolThe accuracy of English pronunciation is the key index to evaluate the quality of English teaching. Correct pronunciation and smooth language flow are the expectations of every student for English learning. Aiming at the poor effect and slow speed of the original SSD (Single Shot MultiBox Detector) algorithm in English teaching pronunciation detection, this paper proposes a clustering and improved SSD algorithm for English teaching pronunciation detection and recognition. The algorithm improves the concept module to enhance the feature extraction ability of the network and improve the detection speed. Meanwhile, it integrates multiscale features to realize multilayer multiplexing and equalization of features, so as to improve the detection effect of small target sound. This algorithm extracts more features by introducing channel attention mechanism, which increases the detection accuracy while reducing computation. In order to optimize the network’s ability to extract target location information, K-means clustering method is used to set the default parameters that are more in line with the characteristics of target samples. The experimental results showed that the proposed algorithm can accurately evaluate the pronunciation quality of reading aloud, so as to effectively reflect the oral English level of the reader.http://dx.doi.org/10.1155/2022/1626229 |
| spellingShingle | Dongxiao Peng An English Teaching Pronunciation Detection and Recognition Algorithm Based on Cluster Analysis and Improved SSD Journal of Electrical and Computer Engineering |
| title | An English Teaching Pronunciation Detection and Recognition Algorithm Based on Cluster Analysis and Improved SSD |
| title_full | An English Teaching Pronunciation Detection and Recognition Algorithm Based on Cluster Analysis and Improved SSD |
| title_fullStr | An English Teaching Pronunciation Detection and Recognition Algorithm Based on Cluster Analysis and Improved SSD |
| title_full_unstemmed | An English Teaching Pronunciation Detection and Recognition Algorithm Based on Cluster Analysis and Improved SSD |
| title_short | An English Teaching Pronunciation Detection and Recognition Algorithm Based on Cluster Analysis and Improved SSD |
| title_sort | english teaching pronunciation detection and recognition algorithm based on cluster analysis and improved ssd |
| url | http://dx.doi.org/10.1155/2022/1626229 |
| work_keys_str_mv | AT dongxiaopeng anenglishteachingpronunciationdetectionandrecognitionalgorithmbasedonclusteranalysisandimprovedssd AT dongxiaopeng englishteachingpronunciationdetectionandrecognitionalgorithmbasedonclusteranalysisandimprovedssd |