Music Genre Classification Using Light Gradient Boosting Machine: A Pilot Study-Reference-Cited by-同舟云学术

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Music Genre Classification Using Light Gradient Boosting Machine: A Pilot Study

Published:2022 Issue: Volume: Page:733-748
ISSN:2367-4512
Container-title:Machine Intelligence and Data Science Applications
language:
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Author:

Sibi Akhil,Singh Rahul,Anurag Kumar,Choudhary Ankur,Prakash Agrawal Arun,Raj Gaurav

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-2347-0_57

Reference13 articles.

1. https://www.kaggle.com/andradaolteanu/gtzan-dataset-music-genre-classification

2. Tzanetakis G, Cook P (2002) Musical genre classification of audio signals. IEEE Trans Speech Audio Process 10:293–302. https://doi.org/10.1109/TSA.2002.800560

3. Li T, Ogihara M, Li Q (2003) A comparative study on content-based music genre classification, pp 282–289. https://doi.org/10.1145/860435.860487

4. Cataltepe Z, Yaslan Y, Sonmez A (2007) Music genre classification using MIDI and audio features. EURASIP J Adv Signal Process. https://doi.org/10.1155/2007/36409

5. Elbir A, Bilal Çam H, Emre Iyican M, Öztürk B, Aydin N (2018) Music genre classification and recommendation by using machine learning techniques. In: 2018 innovations in intelligent systems and applications conference (ASYU), 2018, pp 1–5. https://doi.org/10.1109/ASYU.2018.8554016.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comparative Evaluation of Various Models for the Classification of Music Genre;2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA);2023-08-03

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