基于基本情绪状态信息的说话人验证

P. Staroniewicz
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引用次数: 3

摘要

本文给出了六种基本情绪状态的说话人验证结果。采用基于MFCC特征和GMM分类器的典型说话人验证系统,对情绪言语数据库(愤怒、悲伤、快乐、恐惧、厌恶、惊讶六种行为状态)和中性状态进行了检测。所得结果与主观和客观情绪识别分数进行对比。激活因子强的情绪对说话人识别得分的显著影响更大。
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Considering basic emotional state information in speaker verification
The paper presents speaker verification results for six basic emotional states. The database of emotional speech (six acted states: anger, sadness, happiness, fear, disgust, surprise) plus the neutral state were examined with a typical speaker verification system based on MFCC features and GMM classifiers. The obtained results were confronted with the subjective and objective emotion recognition scores. The significant influence of emotion on speaker recognition scores is substantially bigger for emotions with a strong activation factor.
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