Music Genre Classification: A Comparative Study Between Deep Learning and Traditional Machine Learning Approaches

2021 ◽  
pp. 239-247
Author(s):  
Dhevan S. Lau ◽  
Ritesh Ajoodha
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Comparative Study ◽  
Learning Approaches ◽  
Genre Classification ◽  
Music Genre ◽  
Music Genre Classification

scholarly journals Music Genre Classification using Optimized Sequential Neural Network

2021 ◽  
Vol 10 (3) ◽  
pp. 1949-1958
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Learning Approaches ◽  
Human Beings ◽  
Advantages And Disadvantages ◽  
Genre Classification ◽  
Music Genre ◽  
Music Genre Classification

Music makes up a huge portion of the contents stored and used over the internet, with several sites and applications developed solely to provide music-related services to their users/ customers.Some of the most challenging tasks in this scenario would include music classification based on languages and genres, playlist suggestions based on music history, song suggestions based on playlist contents, top genres / songs based on listeners' rating, likes, number of streams, song loops, popularity of artists based on number of songs released per year, hit songs per year, etc. One of the most important stages to solve the above-mentioned challenges would be music genre classification. It would be impractical to analyze each and every song in a given database to identify and classify music genres, even though human beings are better at performing such tasks. Hence, useful Machine Learning algorithms and Deep Learning approaches may be used for accomplishing such tasks with ease. A thorough analysis to understand the different uses of Machine Learning and Deep Learning algorithms and relevance of such algorithms with respect to situations would be made to highlight and contrast the advantages and disadvantages of each approach. The outcomes of the optimized models would be visualized and comparedto the expected outcomes for better perception.

scholarly journals Music Genre Classification Using Deep Learning with KNN

2021 ◽  
pp. 224-230
Author(s):  
Dr. S. Ponlatha ◽  
Mathisalini B ◽  
Deepthisri K. A ◽  
Kalaiyarasi. M ◽  
Kowshika. V
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Machine Learning Techniques ◽  
Music Score ◽  
Genre Classification ◽  
Learning Techniques ◽  
Music Genre ◽  
The Right ◽  
Music Streaming ◽  
Music Genre Classification

Music genre is a conventional category that predicts the genre of music belonging to tradition or set of conventions. A music platform, with total assets of $26 billion, is ruling the music streaming stage today. At present, it has a huge number of tunes and it is information base and claims to have the right music score for everybody. Like, Spotify, Amazon music, Wynk has put a great deal in examination to further develop the manner in which clients find and pay attention to music. AI is at the centre of their examination. From NLP to Collaborative sifting to Deep Learning, All music platforms utilizes them all. Tunes are examined dependent on their advanced marks for certain elements, including rhythm, acoustics, energy, danceability, and so forth, to answer that incomprehensible old first-date inquiry. Organizations these days use music arrangement, either to have the option to put suggestions to their clients (like Spotify, Soundcloud) or just as an item (for instance, Shazam). Deciding music sorts is the initial phase toward that path. AI procedures have ended up being very fruitful in removing patterns and examples from a huge information pool. Similar standards are applied in Music Analysis moreover. Machine learning techniques are achieved in some recent years and rarely in deep learning. Most of the current music genre classification uses Machine learning techniques. In this, we present a music dataset which includes many genres like Rock, Pop, folk, Classical and many genres. A Deep learning approach is used in order to train and classify the system using KNN.

Automatic Music Genre Classification Based on Linguistic Frequencies Using Machine Learning

2021 ◽  
Author(s):  
Mekala Srinivasa Rao ◽  
O. Pavan Kalyan ◽  
N. Naresh Kumar ◽  
Md. Tasleem Tabassum ◽  
B. Srihari
Keyword(s):  
Machine Learning ◽  
Genre Classification ◽  
Music Genre ◽  
Music Genre Classification

Ensemble of deep learning, visual and acoustic features for music genre classification

2018 ◽  
Vol 47 (4) ◽  
pp. 383-397 ◽  
Author(s):  
Loris Nanni ◽  
Yandre M. G. Costa ◽  
Rafael L. Aguiar ◽  
Carlos N. Silla ◽  
Sheryl Brahnam
Keyword(s):  
Deep Learning ◽  
Acoustic Features ◽  
Genre Classification ◽  
Music Genre ◽  
Music Genre Classification
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