Application of efficient recognition algorithm based on deep neural network in English teaching scene
The recognition of English texts in teaching scenes is a practical research direction. English text recognition can be widely used in English teaching scenes, such as assisting teachers to recognise students’ English homework, text positioning before text translation, developing outdoor classrooms,...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | Connection Science |
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| Online Access: | http://dx.doi.org/10.1080/09540091.2022.2088699 |
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| _version_ | 1849736413148348416 |
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| author | Mengyang Qin |
| author_facet | Mengyang Qin |
| author_sort | Mengyang Qin |
| collection | DOAJ |
| description | The recognition of English texts in teaching scenes is a practical research direction. English text recognition can be widely used in English teaching scenes, such as assisting teachers to recognise students’ English homework, text positioning before text translation, developing outdoor classrooms, assisting junior students in scene understanding and so on. To identify English information in different scenes as accurately as possible, identifying the corresponding text content is the key. Based on a deep neural network, this paper proposes GCN-Attention English recognition algorithm. The experiment adopts the deep learning framework Tensorflow, which combines 104 × 104 size GCN with an attention mechanism for training. The output of GCN is used to train the cyclic neural network to continuously predict the next most likely letter in the sequence. The goal of training is to match the output words with the expected words as much as possible. The test results show that the model can have a good recognition accuracy for the scene image data set used in teaching. |
| format | Article |
| id | doaj-art-89ac72dc052f49e6bfc4cb1b73f95e19 |
| institution | DOAJ |
| issn | 0954-0091 1360-0494 |
| language | English |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Connection Science |
| spelling | doaj-art-89ac72dc052f49e6bfc4cb1b73f95e192025-08-20T03:07:17ZengTaylor & Francis GroupConnection Science0954-00911360-04942022-12-013411913192810.1080/09540091.2022.20886992088699Application of efficient recognition algorithm based on deep neural network in English teaching sceneMengyang Qin0Henan Vocational College of AgricultureThe recognition of English texts in teaching scenes is a practical research direction. English text recognition can be widely used in English teaching scenes, such as assisting teachers to recognise students’ English homework, text positioning before text translation, developing outdoor classrooms, assisting junior students in scene understanding and so on. To identify English information in different scenes as accurately as possible, identifying the corresponding text content is the key. Based on a deep neural network, this paper proposes GCN-Attention English recognition algorithm. The experiment adopts the deep learning framework Tensorflow, which combines 104 × 104 size GCN with an attention mechanism for training. The output of GCN is used to train the cyclic neural network to continuously predict the next most likely letter in the sequence. The goal of training is to match the output words with the expected words as much as possible. The test results show that the model can have a good recognition accuracy for the scene image data set used in teaching.http://dx.doi.org/10.1080/09540091.2022.2088699english textdeep neural networkgcnattention mechanism |
| spellingShingle | Mengyang Qin Application of efficient recognition algorithm based on deep neural network in English teaching scene Connection Science english text deep neural network gcn attention mechanism |
| title | Application of efficient recognition algorithm based on deep neural network in English teaching scene |
| title_full | Application of efficient recognition algorithm based on deep neural network in English teaching scene |
| title_fullStr | Application of efficient recognition algorithm based on deep neural network in English teaching scene |
| title_full_unstemmed | Application of efficient recognition algorithm based on deep neural network in English teaching scene |
| title_short | Application of efficient recognition algorithm based on deep neural network in English teaching scene |
| title_sort | application of efficient recognition algorithm based on deep neural network in english teaching scene |
| topic | english text deep neural network gcn attention mechanism |
| url | http://dx.doi.org/10.1080/09540091.2022.2088699 |
| work_keys_str_mv | AT mengyangqin applicationofefficientrecognitionalgorithmbasedondeepneuralnetworkinenglishteachingscene |