最尤推定法を用いたトイレ内異常音の検出

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2023/09/01

タイトル(英語): Detection of Abnormal Sound in a Public Lavatory Using Maximum Likelihood Estimation

著者名: 森山　剛（東京工芸大学），堀内　紀香（東京工芸大学），綱島　宣浩（（株）ティービーアイ）

著者名(英語): Tsuyoshi Moriyama (Tokyo Polytechnic University), Norika Horiuchi (Tokyo Polytechnic University), Nobuhiro Tsunashima (TB-eye Ltd.)

キーワード: 防犯，監視，遊技施設，異常音検出，スペクトル特徴量，最尤推定法　　security，surveillance，amusement facility，abnormal sound detection，spectral features，maximum likelihood estimation

要約(英語): Amusement facilities such as pachinko parlors have been suffered from one of the social problems where a part of the customers got stressed out by failing their games and carried out destruction of the facility such as lavatories. Solving the problem by visual surveillance using monitoring cameras is not ideal from the viewpoint of privacy. Instead, detecting abnormal sounds which come from those destruction could be the alternative. This work collected all the sounds that could be generated in a public lavatory and analyzed their acoustic characteristics to obtain their statistical distribution. A proposed method of discriminating abnormal sounds utilizes the statistical distribution of the acoustic parameters using Gaussian mixture models to describe them mathematically. An experimental result regarding discriminating abnormal sounds demonstrated the significance of the proposed method.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.143 No.9 （2023） 特集：知能メカトロニクス分野と連携する知覚情報技術

本誌掲載ページ: 909-913 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/143/9/143_909/_article/-char/ja/