hara_CASPer15_final_rev2.pdf 1020 KB
This paper presents a sound collection system to visualize environmental sounds that are collected using a crowd-sourcing approach. An analysis of physical features is generally used to analyze sound properties; however, human beings not only analyze but also emotionally connect to sounds. If we want to visualize the sounds according to the characteristics of the listener, we need to collect not only the raw sound, but also the subjective feelings associated with them. For this purpose, we developed a sound collection system using a crowdsourcing approach to collect physical sounds, their statistics, and subjective evaluations simultaneously. We then conducted a sound collection experiment using the developed system on ten participants.We collected 6,257 samples of equivalent loudness levels and their locations, and 516 samples of sounds and their locations. Subjective evaluations by the participants are also included in the data. Next, we tried to visualize the sound on a map. The loudness levels are visualized as a color map and the sounds are visualized as icons which indicate the sound type. Finally, we conducted a discrimination experiment on the sound to implement a function of automatic conversion from sounds to appropriate icons. The classifier is trained on the basis of the GMM-UBM (Gaussian Mixture Model and Universal Background Model) method. Experimental results show that the F-measure is 0.52 and the AUC is 0.79.
© © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The article has been accepted for publication.
Published in:Pervasive Computing and Communication Workshops (PerCom Workshops), 2015 IEEE International Conference on;
Date of Conference:23-27 March 2015;
Page(s):390 - 395;
Conference Location : St. Louis, MO, USA;
Publisher URL:http://dx.doi.org/10.1109/PERCOMW.2015.7134069 ;
© Copyright 2015 IEEE - All rights reserved.
Proceedings of 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)