Design and development of doctor’s dictation kit using raspberry PI
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.
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| Формат: | Дисертація |
| Мова: | English |
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BRAC University
2017
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| Онлайн доступ: | http://hdl.handle.net/10361/8529 |
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10361-8529 |
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10361-85292022-01-26T10:21:48Z Design and development of doctor’s dictation kit using raspberry PI Haque, Kazi Injamamul Saha, Ullash Biswas, Sudipto Billah, Md. Muhtasim Momin, Abu Saleh Al Rahman, Mohammad Zahidur Islam, Samiul Department of Computer Science and Engineering, BRAC University Raspberry PI Medical dictation Natural language Telepharmacy This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016. Cataloged from PDF version of thesis report. Includes bibliographical references (pages 49-51). Natural language processing and speech to text can make a significant improve in medical dictation (transcription, radiology report, prescription etc) in a developing country like Bangladesh. In the field of telemedicine it can play a very crucial part in the absence of qualified doctors and specialists to prescribe medicine and provide with medical support in remote and rural places. This paper is based on a real time speech detection with a standalone system to implement it in a single board computer Raspberry PI that can also work in crowded place. The recognition engine used for the system is JULIUS along with the toolkit HTK to manipulate HMM(Hidden Markov Model). The acoustic model is set to such a way that it can detect selected medicine names those are widely used in Bangladesh. The accuracy rate of our trained dictionary is 84% but a silent environment and longer string prodeces 94% accuraccy which can also be imroved with more accurate training with advanced directional microphone. The intention of implementing the system in Raspberry PI was to have a future innovation of a standalone device for medical dictation and telepharmacy. Kazi Injamamul Haque Ullash Saha Sudipto Biswas Md. Muhtasim Billah Abu Saleh Al Momin B. Computer Science and Engineering 2017-11-22T10:20:21Z 2017-11-22T10:20:21Z 2016 2016 Thesis ID 13101103 ID 13101156 ID 13101159 ID 13101167 ID 13101220 http://hdl.handle.net/10361/8529 en BRAC University thesis 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. 72 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Raspberry PI Medical dictation Natural language Telepharmacy |
| spellingShingle |
Raspberry PI Medical dictation Natural language Telepharmacy Haque, Kazi Injamamul Saha, Ullash Biswas, Sudipto Billah, Md. Muhtasim Momin, Abu Saleh Al Design and development of doctor’s dictation kit using raspberry PI |
| description |
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016. |
| author2 |
Rahman, Mohammad Zahidur |
| author_facet |
Rahman, Mohammad Zahidur Haque, Kazi Injamamul Saha, Ullash Biswas, Sudipto Billah, Md. Muhtasim Momin, Abu Saleh Al |
| format |
Thesis |
| author |
Haque, Kazi Injamamul Saha, Ullash Biswas, Sudipto Billah, Md. Muhtasim Momin, Abu Saleh Al |
| author_sort |
Haque, Kazi Injamamul |
| title |
Design and development of doctor’s dictation kit using raspberry PI |
| title_short |
Design and development of doctor’s dictation kit using raspberry PI |
| title_full |
Design and development of doctor’s dictation kit using raspberry PI |
| title_fullStr |
Design and development of doctor’s dictation kit using raspberry PI |
| title_full_unstemmed |
Design and development of doctor’s dictation kit using raspberry PI |
| title_sort |
design and development of doctor’s dictation kit using raspberry pi |
| publisher |
BRAC University |
| publishDate |
2017 |
| url |
http://hdl.handle.net/10361/8529 |
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1814309477488263168 |