Predicting regional accents of Bengali language using deep learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Detalles Bibliográficos
Autores principales:	Ibrahim, Md. Abu, Nayeem, Md. Nawaz-S-Salekeen, Al Arabi, Sadaf
Otros Autores:	Mostakim, Moin
Formato:	Tesis
Lenguaje:	English
Publicado:	Brac University 2022
Materias:	Deep learning Bengali accent Accent prediction Neural networks MLP CNN RNN ASR Cognitive learning theory (Deep learning) Artificial intelligence Automatic speech recognition
Acceso en línea:	http://hdl.handle.net/10361/15872

id	10361-15872
record_format	dspace
spelling	10361-158722022-01-26T10:10:26Z Predicting regional accents of Bengali language using deep learning Ibrahim, Md. Abu Nayeem, Md. Nawaz-S-Salekeen Al Arabi, Sadaf Mostakim, Moin Rashid, Warida Department of Computer Science and Engineering, Brac University Deep learning Bengali accent Accent prediction Neural networks MLP CNN RNN ASR Cognitive learning theory (Deep learning) Artificial intelligence Automatic speech recognition This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 39-40). Accent is a huge challenge in communication for all languages. Different people who speak the same language might pronounce the same word differently. In a conversation, if two people are from different regions and they have different accents, we can use our intuition to make sense of what the other person is saying. Sometimes, even our intuition cannot help determining the meaning of the words because of the difference in accent. Therefore, it is extremely difficult for an ASR (Automatic Speech Recognition) system to properly understand the words when the speaker uses different accent instead of the standard or formal accent as most of the time the ASR systems are trained on the formal or standard language. Now a days, most of these issues caused by accents are somewhat worked upon in most used languages like English, Mandarin and few other languages. However, the ASR systems used for Bengali Language is still at its infancy and different accents are a major issue. Finding audio features that differentiate the accents from one another and creating models to predict the accent using Deep Learning techniques will help to create a much better ASR System for Bengali Language. This paper will emphasize on creating few models which can determine the regional accent of Bengali language given an audio sample. Furthermore, after getting the accuracy of the individual models we can choose the model which results in the most accuracy. Further work can be done based on the models to create an ASR System for Bengali language which will be able to handle few more accents than the standard one. Md. Abu Ibrahim Md. Nawaz-S-Salekeen Nayeem Sadaf Al Arabi B. Computer Science 2022-01-12T06:33:19Z 2022-01-12T06:33:19Z 2021 2021-09 Thesis ID 17301157 ID 17301082 ID 17301216 http://hdl.handle.net/10361/15872 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. 40 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Deep learning Bengali accent Accent prediction Neural networks MLP CNN RNN ASR Cognitive learning theory (Deep learning) Artificial intelligence Automatic speech recognition
spellingShingle	Deep learning Bengali accent Accent prediction Neural networks MLP CNN RNN ASR Cognitive learning theory (Deep learning) Artificial intelligence Automatic speech recognition Ibrahim, Md. Abu Nayeem, Md. Nawaz-S-Salekeen Al Arabi, Sadaf Predicting regional accents of Bengali language using deep learning
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
author2	Mostakim, Moin
author_facet	Mostakim, Moin Ibrahim, Md. Abu Nayeem, Md. Nawaz-S-Salekeen Al Arabi, Sadaf
format	Thesis
author	Ibrahim, Md. Abu Nayeem, Md. Nawaz-S-Salekeen Al Arabi, Sadaf
author_sort	Ibrahim, Md. Abu
title	Predicting regional accents of Bengali language using deep learning
title_short	Predicting regional accents of Bengali language using deep learning
title_full	Predicting regional accents of Bengali language using deep learning
title_fullStr	Predicting regional accents of Bengali language using deep learning
title_full_unstemmed	Predicting regional accents of Bengali language using deep learning
title_sort	predicting regional accents of bengali language using deep learning
publisher	Brac University
publishDate	2022
url	http://hdl.handle.net/10361/15872
work_keys_str_mv	AT ibrahimmdabu predictingregionalaccentsofbengalilanguageusingdeeplearning AT nayeemmdnawazssalekeen predictingregionalaccentsofbengalilanguageusingdeeplearning AT alarabisadaf predictingregionalaccentsofbengalilanguageusingdeeplearning
_version_	1814307727580594176

Predicting regional accents of Bengali language using deep learning

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