@inproceedings{4b4c348d7daf4b4f94a2047872e4192d,
title = "Sound-event classification using pseudo-color CENTRIST feature and classifier selection",
abstract = "Sound-event classification often extracts features from an image-like spectrogram. Recent approaches such as spectrogram image feature and subband-power-distribution image feature extract local statistics such as mean and variance from the spectrogram. We argue that such simple image statistics cannot well capture complex texture details of the spectrogram. Thus, we propose to extract pseudo-color CENTRIST features from the logarithm of Gammatone-like spectrogram. To well classify the sound event under the unknown noise condition, we propose a classifier-selection scheme, which automatically selects the most suitable classifier. The proposed approach is compared with the state of the art on the RWCP database, and demonstrates a superior performance.",
keywords = "Classifier Selection, Pseudo-Color CENTRIST Feature, Sound-Event Classification",
author = "Jianfeng Ren and Xudong Jiang and Junsong Yuan",
note = "Publisher Copyright: {\textcopyright} 2016 SPIE.; 1st International Workshop on Pattern Recognition ; Conference date: 11-05-2016 Through 13-05-2016",
year = "2016",
doi = "10.1117/12.2242357",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Xudong Jiang and Guojian Chen and Chiharu Ishii and Genci Capi",
booktitle = "First International Workshop on Pattern Recognition",
address = "United States",
}