Neural Network Music Genre Classification

Pelchat, Nikki; Gelowitz, Craig M.

doi:10.1109/ccece.2019.8861555

Cited by 17 publications

(4 citation statements)

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“…Deep learning is a technological method based on deep neural networks that can simulate how the human brain collects deep-level properties of samples to precisely understand sample distribution, and its impact is superior to typical machine learning algorithms [15]. Neural networks are defined by simulating the patterns of information transmission and processing among neurons in the human brain.…”

Section: Deep Learning Conceptsmentioning

confidence: 99%

A Deep Learning-Enabled Composition System Based on Piano Score Recognition

Shang

2022

Mobile Information Systems

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Piano is used for music and comprises a stringed keyboard instrument wherein the strings are tapped by softer-coated wooden hammers. The score providing music for the piano, often a compressed transcription of orchestral music, is referred to as piano score. Presently, the Internet is overflowing with music score resources. Having so many music score resources available, professional learners and amateur music lovers are unable to identify and obtain music score information that matches their needs and wasting valuable time. Due to the rapid development of deep learning algorithms, some individuals utilize these algorithms to detect piano scores and construct composition systems, reducing the need of traditional machine learning algorithms on manual design and music knowledge guidelines. This paper uses the deep learning algorithm to construct piano score recognition framework based on K-Nearest Neighbor (KNN) algorithm and formulates the recognition system into multinote that significantly improves the recognition rate for the system. The self-attention mechanism is then introduced in order to build a composition system based on a deep learning algorithm in which composition training and processes are described. Finally, a comparative experiment is conducted to evaluate the recognition accuracy for the KNN-based piano score recognition system. The results show that highest recognition accuracy of this system is 67.5%. The effect of composition system is evaluated based on prediction accuracy of notes. Three experiments are conducted to train the composition notes. As a result, the prediction accuracy of experiments 1, 2, and 3 is 89.2%, 91.8%, and 92.7%, respectively, indicating that the system has a high prediction accuracy and a perfect composition effect.

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Section: Deep Learning Conceptsmentioning

confidence: 99%

A Deep Learning-Enabled Composition System Based on Piano Score Recognition

Shang

2022

Mobile Information Systems

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“…Subsequently, the researchers continued to prove that CNN gave good results in pattern recognition [60,61] (digit recognition, alpha numeric, traffic signs and other classes of objects). Recently, CNN has been applied a lot in the field of classifying music by genre [28,[62][63][64][65].…”

Section: Convolutional Neural Network (Cnn)mentioning

confidence: 99%

Automatic Identification of Some Vietnamese Folk Songs Cheo and Quanho Using Convolutional Neural Networks

Thành

Loan

Thuy

2022

JCC

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We can say that music in general is an indispensable spiritual food in human life. For Vietnamese people, folk music plays a very important role, it has entered the minds of every Vietnamese person right from the moment of birth through lullabies for children. In Vietnam, there are many different types of folk songs that everyone loves, and each has many different melodies. In order to archive and search music works with a very large quantity, including folk songs, it is necessary to automatically classify and identify those works. This paper presents the method of determining the feature parameters and then using the convolution neural network (CNN) to classify and identify some Vietnamese folk tunes as Quanho and Cheo. Our experimental results show that the average highest classification and identification accuracy are 99.92% and 97.67%, respectivel.

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“…As a result, well-known applications like Napster, Spotify, and Soundcloud, apply genre classification to recommend music to their users. Deep Neural Network, CNN has been popularly used for classifying music [5] [6] [7] over the years. In our research, we proposed a model BMNet-5 which is a deep neural network with 5 layer neuron to extract Bangla music genre.…”

Section: Introductionmentioning

confidence: 99%

BMNet-5: A Novel Approach of Neural Network to Classify the Genre of Bengali Music Based on Audio Features

et al. 2022

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Music genre classification (MGC) is the process of putting genre labels on music by analyzing the sounds or words. With the rapid growth of music data repositories, MGC can be used in a lot of ways to organize and manage music recommendation systems, advertising, and streaming services. But there have been a lot of works on classifying English music using different statistical and machine learning methods, but there hasn't been much progress in classifying Bengali music. Also, Deep Learning (DL) methods have been used in a few important ways to classify different types of music. The content and uniqueness of Bengali music make it much more interesting. Also, there is still a lot to learn about how to use the DL approach in Bengali music. So, Bengali music genre classification is a pretty new area of research in the field of Deep Learning. In this paper, we developed a unique technique called BMNet-5 to perform a multiclass classification of Bangla music genres such as "Bangla Adhunik," "Bangla Hip-Hop," "Bangla Band Music," "Nazrulgeeti," "Palligeeti," and "Rabindra Sangeet." We show the effectiveness of the suggested technique by extracting features from a dataset of 1742 Bangla music pieces and evaluating the automated classification judgments. The proposed BMNet-5 is based on a neural network designed to predict music genre from audio inputs. Our suggested model outperformed the corresponding previous research with an accuracy of 90.32%. The BMNet-5 model is then tested for performance consistency using K-fold cross validation with varying k values. Finally, we use the suggested model to train the interpretable SHAP model for all the genre of the Bangla music dataset, and the development of an explainable outcome may have a significant advantage.

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Neural Network Music Genre Classification

Cited by 17 publications

References 1 publication

A Deep Learning-Enabled Composition System Based on Piano Score Recognition

A Deep Learning-Enabled Composition System Based on Piano Score Recognition

Automatic Identification of Some Vietnamese Folk Songs Cheo and Quanho Using Convolutional Neural Networks

BMNet-5: A Novel Approach of Neural Network to Classify the Genre of Bengali Music Based on Audio Features

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