@inproceedings{oai:kutarr.kochi-tech.ac.jp:00000737,
 author = {佐藤, 公信 and 竹田, 史章},
 book = {情報処理学会研究報告：音楽情報科学},
 issue = {19},
 month = {Feb},
 note = {本研究は新たな声紋認証手法の開発を目的とする．提案システムは特徴量抽出に Fast Fourier Transform を用い，識別器に未知のパターンに対して排除能力が優れた Radial Basis Function Networks(RBFN) を用いる．提案手法は RBFN の出力細胞数を 1 としているために，特定個人の認識と未知のパターンの排除に優れると予測される．実験により認証対象者となる被験者の未学習データを評価し，提案手法の認証率および排除率を確認する．, The purpose of this study is development of a new voice verification method. Fast Fourier Trasform is used for the feature extraction method in the proposed system. Radial Basis Function Networks (RBFN), which is known that the rejection rate for the unknown pattern is hight, is used for the classifier of the proposed method. Especially, the number of the output cell of the RBFN is only one. Therefore, the proposed method excel as certification of specific person and rejection of the unknown person. In the experiment, the verification rate and rejection rate of the proposed system is confirmed using unknown pattern of subjects who will be verified.},
 publisher = {情報処理学会},
 title = {学習により自己チューニング可能なRadial-Basis Function Networksによる声紋認証手法の提案},
 volume = {2011-MUS-89},
 year = {2011}
}