A study on the efficacy of natural language generation techniques for similar writing personalities
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.
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| Langue: | English |
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Brac University
2024
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| Accès en ligne: | http://hdl.handle.net/10361/22884 |
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10361-228842024-05-20T21:02:28Z A study on the efficacy of natural language generation techniques for similar writing personalities Anwar, Ahmed Tanzir, Hasan Mohammod Hosain, Abdul Halim Islam, Taslima Raya, Nusrat Zaman Sadeque, Farig Yousuf Department of Computer Science and Engineering, Brac University Natural language processing LSTM BanglaBERT BanglaT5 Writing personality T5 model Adversarial attacks Natural language processing (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024. Cataloged from PDF version of thesis. Includes bibliographical references (pages 100-101). Over the past two decades, the domain of Natural Language Processing has undergone a remarkable transformation enabling machines to generate text, summarize content, paraphrase and analyze sentiment. The captivating idea of analyzing and copying someone’s writing style is no longer impossible. Pushing boundaries further, we have embarked on a journey to implement such a model for the Bengali language by utilizing the approach of style transfer through the application of deep learning using LLM. One’s writing personality can be identified by training the model by imputing a set of documents (notes, books, etc) authored by the writers only. The system will be able to extract important information to recreate sentences with similar structural properties used by the author. Additionally, it will also be able to detect whether a particular sentence structure synchronizes with that author’s distinctive style. The outcome of our model aims to fulfill the need of a particular writing taste of an author, as requested by the user. In essence, our model blends technology and art to write in a way that is reminiscent of their favorite Bengali author. Our proposed model not only skillfully excels in authorship classification and mimicking their style, but also stands resilient against potential adversarial attacks, making it a strong and unyielding system that aligns well with our research objective. Ahmed Anwar Hasan Mohammod Tanzir Abdul Halim Hosain Taslima Islam Nusrat Zaman Raya B.Sc in Computer Science 2024-05-20T06:11:33Z 2024-05-20T06:11:33Z ©2024 2024-01 Thesis ID: 20301077 ID: 20101598 ID: 20101300 ID: 20101603 ID: 23241034 http://hdl.handle.net/10361/22884 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. 108 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Natural language processing LSTM BanglaBERT BanglaT5 Writing personality T5 model Adversarial attacks Natural language processing (Computer science) |
| spellingShingle |
Natural language processing LSTM BanglaBERT BanglaT5 Writing personality T5 model Adversarial attacks Natural language processing (Computer science) Anwar, Ahmed Tanzir, Hasan Mohammod Hosain, Abdul Halim Islam, Taslima Raya, Nusrat Zaman A study on the efficacy of natural language generation techniques for similar writing personalities |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024. |
| author2 |
Sadeque, Farig Yousuf |
| author_facet |
Sadeque, Farig Yousuf Anwar, Ahmed Tanzir, Hasan Mohammod Hosain, Abdul Halim Islam, Taslima Raya, Nusrat Zaman |
| format |
Thesis |
| author |
Anwar, Ahmed Tanzir, Hasan Mohammod Hosain, Abdul Halim Islam, Taslima Raya, Nusrat Zaman |
| author_sort |
Anwar, Ahmed |
| title |
A study on the efficacy of natural language generation techniques for similar writing personalities |
| title_short |
A study on the efficacy of natural language generation techniques for similar writing personalities |
| title_full |
A study on the efficacy of natural language generation techniques for similar writing personalities |
| title_fullStr |
A study on the efficacy of natural language generation techniques for similar writing personalities |
| title_full_unstemmed |
A study on the efficacy of natural language generation techniques for similar writing personalities |
| title_sort |
study on the efficacy of natural language generation techniques for similar writing personalities |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/22884 |
| work_keys_str_mv |
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