About: Bag-of-features models based on C-DNN network for acoustic scene classification

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type	http://eprints.org/ontology/ConferenceItemEPrint http://eprints.org/ontology/EPrint Article Academic Article
seeAlso	HTML Summary of #91420 Bag-of-features models based on C-DNN network for acoustic scene classification
Title	Bag-of-features models based on C-DNN network for acoustic scene classification
described by	https://demo.openlinksw.com/about/id/entity/https/www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3
Date	2019-06-08
Creator	I. McLoughlin Yue Lang Lam Dang Pham Palaniappan Ramaswamy
status	peer reviewed published
abstract	This work proposes bag-of-features deep learning models for acoustic scene classi?cation (ASC) – identifying recording locations by analyzing background sound. We explore the effect on classi?cation accuracy of various front-end feature extraction techniques, ensembles of audio channels, and patch sizes from three kinds of spectrogram. The back-end process presents a two-stage learning model with a pre-trained CNN (preCNN) and a post-trained DNN (postDNN). Additionally, data augmentation using the mixup technique is investigated for both the pre-trained and post-trained processes, to improve classi?cation accuracy through increasing class boundary training conditions. Our experiments on the 2018 Challenge on Detection and Classi?cation of Acoustic Scenes and Events - Acoustic Scene Classi?cation (DCASE2018-ASC) subtask 1A and 1B signi?cantly outperform the DCASE2018 reference implementation and approach state-of-the-art performance for each task. Results reveal that the ensemble of multi-spectrogram features and data augmentation is bene?cial to performance.
Is Part Of	https://kar.kent.ac.uk/id/repository
list of authors	https://kar.kent.ac.uk/id/eprint/91420#authors
presented at	2019 AES International Conference on Audio Forensics (June 2019)
is topic of	https://www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #91420 Bag-of-features models based on C-DNN network for acoustic scene classification

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