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Music and Audio Processing
TopicLeading institutions, researchers & key papers
This cluster of papers focuses on the classification and analysis of audio signals, including music genre classification, environmental sound recognition, melody extraction, and acoustic scene classification. It explores techniques such as deep learning, convolutional neural networks, and feature extraction for music information retrieval.
89
Works
IDs:OpenAlex
How has Music and Audio Processing's publication output changed over time?
ScholarIQpublication output · 2004–2025
Output grew0% over the shown period — from 1 works in 2004 to 1 in 2025.
1
1
1
1
1
2
1
2
4
1
2004200920102012201620172018202120222025
What are the most-cited papers on Music and Audio Processing?
ScholarIQmost cited works
SoundSense
Hong Lu, Wei Pan, Nicholas D. Lane, Tanzeem Choudhury, Andrew T. Campbell
2009580 Citations
Very deep convolutional neural networks for raw waveforms
Wei Dai, Chia Dai, Shuhui Qu, Juncheng Li, Samarjit Das
2017340 Citations
Musical genre classification using support vector machines
Changsheng Xu, Namunu C. Maddage, Xi Shao, Fang Cao, Qi Tian
S4363608982. 2004152 Citations
A comparison of Deep Learning methods for environmental sound detection
Juncheng Li, Wei Dai, Florian Metze, Shuhui Qu, Samarjit Das
2017143 Citations
Speaker Gender Recognition Based on Deep Neural Networks and ResNet50
Abeer Ali Alnuaim, Mohammed Zakariah, Chitra Shashidhar, Wesam Atef Hatamleh, Hussam Tarazi, Prashant Kumar Shukla, Rajnish Ratna
S235346. 2022108 CitationsOPEN ACCESS
Where is Music and Audio Processing research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
S4363608982152
S235346108
S11020666979
S1960598633
S2010922923
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
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How much of the research on Music and Audio Processing is open access?
ScholarIQopen access share
20%OPEN ACCESS
Gold
7%
Green
7%
Hybrid
7%
Bronze
0%
Closed
80%
Related on ScholarIQ
SoundSense
Paper
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Paper
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Very deep convolutional neural networks for raw waveforms
Paper
The influence of metricality and modality on synchronization with a beat
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Paper