English  |  正體中文  |  简体中文  |  Items with full text/Total items : 25248/25843 (98%)
Visitors : 5204221      Online Users : 63
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    Please use this identifier to cite or link to this item: http://ir.lib.ksu.edu.tw/handle/987654321/14338


    Title: 以高斯混合模型為基礎之家庭成員語者辨識系統
    Authors: 王建仁
    蔡哲民
    王麒讚
    Keywords: 生物特徵
    數位家庭
    語者辨識
    高斯混合模型
    biometrics
    speaker recognition
    Gaussian mixture model
    digital home
    Date: 2007-11-29
    Issue Date: 2008-01-02 12:41:44 (UTC+8)
    Abstract: 隨著資訊科技的發展方向漸漸由企業導向轉向居家生活導向,使用生物特徵技術來輔助數位家庭之居家保全已非難事。以往的辨識系統大多是利用人的指紋、外型來進行身份辨識。本文提出一個依據家庭成員之聲紋辨識系統,主要是用來進行家庭成員的辨識,並且判斷出是否有外來者。由實驗結果可得知,本系統在辨識家庭成員上有不錯的辨識率。
    Successfully recognizing family members is important for home security. The finger print is unique to each person and is adopted in many human recognition systems. Recognizing people based on various biometrics, such as faces and voices, are also studied extensively and achieve great success.
    In this paper, we proposed a family member recognition system based on the voices. In this system, the speech features are 13th order Mel-Frequency cepstral coefficients. The Gaussian mixture models server as the recognizers. This system achieves 91% for recognizing six family members. 86% family member recognition rate is achieved when four strangers are added into the experiments.
    Appears in Collections:[資訊科技學院 ] 2007年優質家庭生活科技(U-home)之關鍵技術研討會

    Files in This Item:

    File Description SizeFormat
    IE4.pdf219KbAdobe PDF1View/Open


    All items in KSUIR are protected by copyright, with all rights reserved.


    本網站之所有圖文內容授權為崑山科技大學圖書資訊館所有,請勿任意轉載或擷取使用。
    ©Kun Shan University Library and Information Center
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback