Producing self tuned music using machine learning tools
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.
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BRAC University
2018
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| 在线阅读: | http://hdl.handle.net/10361/8886 |
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10361-88862022-01-26T10:04:57Z Producing self tuned music using machine learning tools Tasneem, Akifa Reza, Mostofa Saif Anindya, Navid Mostakim, Moin Kaonain, Md. Shamsul Department of Computer Science and Engineering, BRAC University MFCC Music information retrieval MATLAB GTZAN SVM This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. Cataloged from PDF version of thesis report. Includes bibliographical references (page 20-21). Automatic music genre classification is one of the important tasks for the Music Information Retrieval (MIR). With the development of the knowledge on Machine Learning, researchers have implemented different methods to implement automatic music genre classification. In this paper, we have done secondary research on various papers that have used different mechanisms to achieve results for genre detection. We will check for the performance of genre detection using kNN (k-Nearest Neighbor Classifier) Classifier and the SVM (Support Vector Machine) classifier. We used MATLAB and specific toolboxes made by MIRLab such as Machine Learning Toolbox and Speech and Audio Processing Toolbox and used different kinds of features for classifiers such as MFCC (Mel-frequency cepstral coefficients). We will use the GTZAN dataset to do the classification using the classifiers. This goal is to see which classifier algorithm on MFCC features performs optimally on the GTZAN dataset. We have used various papers as references on this topic. Akifa Tasneem Mostofa Saif Reza Navid Anindya B. Computer Science and Engineering 2018-01-03T05:27:00Z 2018-01-03T05:27:00Z 2017 2017 Thesis ID 13101192 ID 12201106 ID 13101233 http://hdl.handle.net/10361/8886 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. 21 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
MFCC Music information retrieval MATLAB GTZAN SVM |
| spellingShingle |
MFCC Music information retrieval MATLAB GTZAN SVM Tasneem, Akifa Reza, Mostofa Saif Anindya, Navid Producing self tuned music using machine learning tools |
| description |
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. |
| author2 |
Mostakim, Moin |
| author_facet |
Mostakim, Moin Tasneem, Akifa Reza, Mostofa Saif Anindya, Navid |
| format |
Thesis |
| author |
Tasneem, Akifa Reza, Mostofa Saif Anindya, Navid |
| author_sort |
Tasneem, Akifa |
| title |
Producing self tuned music using machine learning tools |
| title_short |
Producing self tuned music using machine learning tools |
| title_full |
Producing self tuned music using machine learning tools |
| title_fullStr |
Producing self tuned music using machine learning tools |
| title_full_unstemmed |
Producing self tuned music using machine learning tools |
| title_sort |
producing self tuned music using machine learning tools |
| publisher |
BRAC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/8886 |
| work_keys_str_mv |
AT tasneemakifa producingselftunedmusicusingmachinelearningtools AT rezamostofasaif producingselftunedmusicusingmachinelearningtools AT anindyanavid producingselftunedmusicusingmachinelearningtools |
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