@inproceedings{d5d92adebc1e48d79cc1f251da28e375,
title = "Robust minimum statistics project coefficients feature for acoustic environment recognition",
abstract = "Acoustic environment recognition has been widely used in many applications, and is a considerable difficult problem for the real-life and complex environment. This paper proposes a novel feature, named minimum statistics project coefficients (MSPC), and intents to solve this problem. The MSPC feature is extracted from the background sound which is more robust than the foreground sound for the task of acoustic environment recognition. Experimental results show the outstanding performance of the MSPC feature compared with the conventional acoustic features, especially in very complex acoustic environments.",
keywords = "Acoustic environment recognition (AER), background sound/noise, minimum statistics, sound event",
author = "Shiwen Deng and Jiqing Han and Chaozhu Zhang and Tieran Zheng and Guibin Zheng",
year = "2014",
doi = "10.1109/ICASSP.2014.6855206",
language = "英语",
isbn = "9781479928927",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "8232--8236",
booktitle = "2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014",
address = "美国",
note = "2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 ; Conference date: 04-05-2014 Through 09-05-2014",
}