Robust minimum statistics project coefficients feature for acoustic environment recognition
Shiwen Deng, Jiqing Han, Chaozhu Zhang, Tieran Zheng, Guibin Zheng · 2014
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.