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Authors: Yu Su 1 ; Jingyu Wang 2 ; Ke Zhang 2 ; Kurosh Madani 3 and Xianyu Wang 2

Affiliations: 1 Northwestern Polytechnical University (NPU), 127 Youyi Xilu, Xi’an 710072, Shaanxi, China, Universit Paris-Est, Signals, Images, and Intelligent Systems Laboratory (LISSI / EA 3956), University Paris-Est Creteil, Senart-FB Institute of Technology, 36-37 rue Charpak, 77127 Lieusaint and France ; 2 Northwestern Polytechnical University (NPU), 127 Youyi Xilu, Xi’an 710072, Shaanxi and China ; 3 Universit Paris-Est, Signals, Images, and Intelligent Systems Laboratory (LISSI / EA 3956), University Paris-Est Creteil, Senart-FB Institute of Technology, 36-37 rue Charpak, 77127 Lieusaint and France

ISBN: 978-989-758-327-8

Keyword(s): Auditory Awareness, Saliency Detection, Deep Learning.

Abstract: Research in the human voice and environment sound recognition has been well studied during the past decades. Nowadays, modeling auditory awareness has received more and more attention. Its basic concept is to imitate the human auditory system to give artificial intelligence the auditory perception ability. In order to successfully mimic human auditory mechanism, several models have been proposed in the past decades. In view of deep learning (DL) algorithms has better classification performance than conventional approaches (such as GMM and HMM), the latest research works mainly focused on building auditory awareness models based on deep architectures. In this survey, we will offer a quality and compendious survey on recent auditory awareness models and development trend. This article includes three parts: i) classical auditory saliency detection method and developments during the past decades, ii) the application of machine learning in ASD. Finally, summarizing comments and development trends in this filed will be given. (More)

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Paper citation in several formats:
Su, Y.; Wang, J.; Zhang, K.; Madani, K. and Wang, X. (2018). Computational Modelling Auditory Awareness.In Proceedings of the 10th International Joint Conference on Computational Intelligence - Volume 1: IJCCI, ISBN 978-989-758-327-8, pages 160-167. DOI: 10.5220/0006925401600167

@conference{ijcci18,
author={Yu Su. and Jingyu Wang. and Ke Zhang. and Kurosh Madani. and Xianyu Wang.},
title={Computational Modelling Auditory Awareness},
booktitle={Proceedings of the 10th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,},
year={2018},
pages={160-167},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006925401600167},
isbn={978-989-758-327-8},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,
TI - Computational Modelling Auditory Awareness
SN - 978-989-758-327-8
AU - Su, Y.
AU - Wang, J.
AU - Zhang, K.
AU - Madani, K.
AU - Wang, X.
PY - 2018
SP - 160
EP - 167
DO - 10.5220/0006925401600167

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