TUNG FANG Institutional Repository:Item 987654321/1918
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    题名: Robust Several-Speaker Speech Recognition with Highly Dependable Online Speaker Adaptation and Identification
    作者: Shih, Po-Yi
    Lin, Po-Chuan
    Wang, Jhing-Fa
    Lin, Yuan-Ning
    林博川
    (東方設計學院電子與資訊系)
    贡献者: 東方設計學院電子與資訊系
    关键词: Speech recognition
    Speaker adaptation
    Speaker identification
    Dependable adaptation
    Confidence score
    日期: 2010-09
    上传时间: 2015-07-14 14:34:23 (UTC+8)
    摘要: The currently adaptive mechanisms adapt a single acoustic model for a speaker in speaker-independent speech recognition system. However, as more users use the same speech recognizer, single acoustic model adaptation leads to negative adaptation upon switching between users. Such a situation is problematic (undependable adaptation). This paper, considering the situation of a smart home or an office with staff members, presents the speaker-specific acoustic model adaptation based on a multi-model mechanism, to solve the problem of undependable adaptation. First, the identification of the current speaker is confirmed using the SVM classifier, then the corresponding acoustic parameters are extracted and integrated with the speaker-independent acoustic model to yield the speaker-dependent acoustic model and speech recognition accuracy then be promoted for the current speaker. To provide dependable adaptation data to achieve online positive speaker adaptation, a mechanism that measures confidence score is designed to verify each recognition result and determined whether it can be an adaptation datum. The experimental results indicate that the proposed system can effectively increase the average speech recognition accuracy from 62% to 85%. Thus, the proposed system can achieve robust several-speaker speech recognition with highly dependable online speaker adaptation and identification.
    關聯: Journal of Network and Computer Applications, Vol.34 no.5, pp.1459–1467
    显示于类别:[電子與資訊系(遊戲動畫系、動畫科)] 期刊論文

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