VGGish Deep Learning Model: Audio Feature Extraction and Analysis
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-3245-6_5
Reference20 articles.
1. Sharma G, Umapathy K, Krishnan S (2020) Trends in au- dio signal feature extraction methods. Appl Acoust 158:107020. https://doi.org/10.1016/j.apacoust.2019.107020
2. Wu Y (2009) New effective method on content-based audio feature extraction. Comput Eng Appl
3. Umapathy K, Krishnan S, Rao RK (2007) Audio signal feature extraction and classification using local discriminant bases 15(4):1236–1246. https://doi.org/10.1109/tasl.2006.885921
4. Liang B, Yanli H, Songyang L, Jianyun C, Lingda W (2005) IEEE 2005 IEEE International Conference on Systems, Man and Cybernetics—Waikoloa, HI, USA (10–12 Oct. 2005)]. In: 2005 IEEE International Conference on Systems, Man and Cybernetics—Feature Analysis and Extraction for Audio Automatic Classification 1:767–772. https://doi.org/10.1109/icsmc.2005.1571239
5. Chu KK, Leung SH (2003) [IEEE ISCAS 2003. “International Symposium on Circuits and Systems—Bangkok, Thailand (25–28 May 2003)]. In: Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS ‘03.—Feature extraction based on perceptually non-uniform spectral compression for speech recognition, 3, III-726–III-729. https://doi.org/10.1109/ISCAS.2003.1205122
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