Computer vision-based Bengali sign language to text generation
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
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| Jazyk: | English |
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Brac University
2022
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| On-line přístup: | http://hdl.handle.net/10361/16941 |
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10361-169412022-06-08T21:01:43Z Computer vision-based Bengali sign language to text generation Tazalli, Tonjih Liya, Sumaya Sadbeen Aunshu, Zarin Anan Hossain, Magfirah Mehjabeen, Zareen Hossain, Muhammad Iqbal Ahmed, Md. Sabbir Department of Computer Science and Engineering, Brac University Bangla sign language Convolutional neural network (CNN) Video classification PyTorch YOLOv5 Image processing Neural networks (Computer science) Image processing -- Digital techniques. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 34-35). In the whole world, around 7% of people have hearing and speech impairment problems. They use sign language as their communication method. People from various countries use a variety of sign languages. As an example, there are ASL, CSL, JSL, etc. Even in our country, there are lots of people born with hearing and speech impairment problems. So, our primary focus is to work for those people by converting Bangla sign language into text. There are already various projects on Bangla sign language done by other people. However, they focused more on the separate alphabets and numerical numbers. That is why we want to concentrate on Bangla word signs since these people prefer to communicate using words or phrases rather than alphabets. There is not any proper database for Bangla word sign language, so we are making a database for Bangla word sign language for our work. In recognition of sign language (SLR), there usually are two types of scenarios: isolated SLR, which takes words by word and completes recognize action, and the other one is continuous SLR, which completes action by translating the whole sentence at once. We are working on isolated SLR. We introduce a method where we are going to use PyTorch and YOLOv5 for a video classification model to convert Bangla sign language into the text from the video where each video has only one sign language word. Here,we have achieved an accuracy rate of 76.29% on the training dataset and 51.44% on the testing dataset. We are working to build a system that will make it easier for hearing and speech-disabled people to interact with the general public. Tonjih Tazalli Sumaya Sadbeen Liya Zarin Anan Aunshu Magfirah Hossain Zareen Mehjabeen B. Computer Science 2022-06-08T04:50:14Z 2022-06-08T04:50:14Z 2022 2022-01 Thesis ID 18101176 ID 18101152 ID 18101183 ID 18301210 ID 21341059 http://hdl.handle.net/10361/16941 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 35 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Bangla sign language Convolutional neural network (CNN) Video classification PyTorch YOLOv5 Image processing Neural networks (Computer science) Image processing -- Digital techniques. |
| spellingShingle |
Bangla sign language Convolutional neural network (CNN) Video classification PyTorch YOLOv5 Image processing Neural networks (Computer science) Image processing -- Digital techniques. Tazalli, Tonjih Liya, Sumaya Sadbeen Aunshu, Zarin Anan Hossain, Magfirah Mehjabeen, Zareen Computer vision-based Bengali sign language to text generation |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. |
| author2 |
Hossain, Muhammad Iqbal |
| author_facet |
Hossain, Muhammad Iqbal Tazalli, Tonjih Liya, Sumaya Sadbeen Aunshu, Zarin Anan Hossain, Magfirah Mehjabeen, Zareen |
| format |
Thesis |
| author |
Tazalli, Tonjih Liya, Sumaya Sadbeen Aunshu, Zarin Anan Hossain, Magfirah Mehjabeen, Zareen |
| author_sort |
Tazalli, Tonjih |
| title |
Computer vision-based Bengali sign language to text generation |
| title_short |
Computer vision-based Bengali sign language to text generation |
| title_full |
Computer vision-based Bengali sign language to text generation |
| title_fullStr |
Computer vision-based Bengali sign language to text generation |
| title_full_unstemmed |
Computer vision-based Bengali sign language to text generation |
| title_sort |
computer vision-based bengali sign language to text generation |
| publisher |
Brac University |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10361/16941 |
| work_keys_str_mv |
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