2024-03-28T18:19:55Zhttps://ipsj.ixsq.nii.ac.jp/ej/?action=repository_oaipmhoai:ipsj.ixsq.nii.ac.jp:001808832023-11-17T02:17:36Z06504:09168:09182
Iterative Outlier Removal Method Using In-Cluster Variance Changes in Multi-Microphone Array Sound Source Localization.eng人工知能と認知科学http://id.nii.ac.jp/1001/00180795/Conference Paperhttps://ipsj.ixsq.nii.ac.jp/ej/?action=repository_action_common_download&item_id=180883&item_no=1&attribute_id=1&file_no=1Copyright (c) 2017 by the Information Processing Society of Japan東工大東工大東工大東工大/ホンダRIJDaniel, Gabriel小島, 諒介干場, 功太郎中臺, 一博In recent studies sound based localization plays a great role in fields such as Robot Audition and Spatial Bird Song Localization. It is difficult to distinguish between a valid sound source and environmental noises. This paper proposes an outlier-robust sound source localization method using multiple microphone arrays. Proposed algorithm has been tested on three datasets: a simulation dataset and two datasets of bird songs recorded in the real environment with different microphone array layouts. The algorithm has been compared with other outlier extraction techniques. We confirmed the effectiveness of the proposed algorithm.AN00349328第79回全国大会講演論文集201712292302017-03-162017-05-22