Music Recommendation Systems: A Survey

Kleć, Mariusz; Wieczorkowska, Alicja

doi:10.1007/978-3-030-66450-3_7

Cited by 5 publications

(2 citation statements)

References 66 publications

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“…In [21], a tutorial on MIR is provided that is especially useful to newcomers in the field. [13], [25] reviews MRS. Music Genre Classification (MGC) is reviewed in [26]. Drum transcription is reviewed in [27], focusing on non-negative matrix factorization and recurrent neural network architectures.…”

Section: B Related Surveysmentioning

confidence: 99%

Music Deep Learning: Deep Learning Methods for Music Signal Processing—A Review of the State-of-the-Art

et al. 2023

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The discipline of Deep Learning has been recognized for its strong computational tools, which have been extensively used in data and signal processing, with innumerable promising results. Among the many commercial applications of Deep Learning, Music Signal Processing has received an increasing amount of attention over the last decade. This work reviews the most recent developments in Deep Learning in Music signal processing. Two main applications that are discussed are Music Information Retrieval, which spans a plethora of applications, and Music Generation, which can fit a range of musical styles. After a review of both topics, several emerging directions are identified for future research.

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Section: B Related Surveysmentioning

confidence: 99%

Music Deep Learning: Deep Learning Methods for Music Signal Processing—A Review of the State-of-the-Art

et al. 2023

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“…Music suggestions are made by comparing one piece of music to another or by o ering priority from one listener to another [3]. e di culty of a music recommendation system is to design a technology that can constantly locate appealing new music while also understanding the consumers' music tastes [4].…”

Section: Introductionmentioning

confidence: 99%

Designing a National Music System for a Smart Concert Hall Using Neural Network and Wireless Internet of Things

Zhang

2022

Scientific Programming

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With the fast advancement of science and technology, numerous music systems have emerged. However, there are few folk music in the music industry, for example, pop music, which leads to the inability of folk music lovers to find their favorite music. For this problem, this paper develops a national system of smart concert hall based on a neural network and wireless Internet of things (IoT). It establishes the architecture model of the wireless IoT system of the concert hall by describing the neural network, neuron model, and BP neural network model in detail. Besides, this paper develops the smart music national system based on this model, completes the functional module design of the national music system, and uses the music attribute recommendation model. Finally, it analyzes the scoring performance of the national music system. The results show that when the number of recommended folk music songs is less than 20, the lowest MAE is 0.73.

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Recommendation Methods for Information Technology Support of Lifelong Learning Situations

Savchenko,

Synytsya,

Savchenko-Synyakova

2023

Lecture Notes on Data Engineering and Communications Technologies

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Music Recommendation Systems: A Survey

Cited by 5 publications

References 66 publications

Music Deep Learning: Deep Learning Methods for Music Signal Processing—A Review of the State-of-the-Art

Music Deep Learning: Deep Learning Methods for Music Signal Processing—A Review of the State-of-the-Art

Designing a National Music System for a Smart Concert Hall Using Neural Network and Wireless Internet of Things

Recommendation Methods for Information Technology Support of Lifelong Learning Situations

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