Music Genre Classification Using CNN and RNN-LSTM-Reference-Cited by-同舟云学术

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Music Genre Classification Using CNN and RNN-LSTM

Published:2022 Issue: Volume: Page:729-745
ISSN:2367-3370
Container-title:Micro-Electronics and Telecommunication Engineering
language:
Short-container-title:

Author:

Gupta Rohan,Ashish Shivam,Shekhar Himanshu,Dominic MS. Deepica S.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-8721-1_67

Reference9 articles.

1. Bahuleyan H (2018) Music genre classification using machine learning techniques, Sound (cs.SD); Audio and speech processing (eess.AS)

2. Reed J, Lee C-H (2006) A study on music genre classification based on universal acoustic models. ISMIR

3. Chang KK, Jang J-SR, Iliopoulos CS (2013) On music genre classification via compressive sampling. 2013 IEEE international conference on multimedia and Expo (ICME)

4. Panagakis Y, Kotropoulos C, Kotropoulos C (2009) Music genre classification using locality preserving non-negative tensor factorization and sparse representations. ISMIR

5. Music Genre Classification. https://www.kaggle.com/c/music-genre-classification/datasets

Cited by 2 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. A hybrid deep learning approach for classification of music genres using wavelet and spectrogram analysis;Neural Computing and Applications;2023-01-19

2. Transformer-based Technique to Classify Raags in Hindustani Classical Music;2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI);2022-12-21

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