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基于Gamma tone滤波和PCNN的说话人识别 被引量:1

Speaker Recognition Based on Gamma Tone Filter and PCNN
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摘要 为了更好地提取说话人的特征,对语音进行滤波的预处理。Gammatone滤波器可以很好地模拟基底膜滤波器的形状,因此采用作为标准耳蜗听觉滤波器的Gammatone滤波器对语谱图进行滤波,再通过脉冲耦合神经网络来提取说话人特征进行分析。仿真结果表明,由该方法得到的说话人的熵序列与自身熵序列的欧氏距离较未经过Gammatone滤波时小,提高了识别率。 In order even better to extract feature parameters of speakers,speech should be filtered as a pre-processing process.Gamma tone filter can well imitate the human basilar membrane's shape,so Gamma tone filter is adopted which is a standard cochlea sense of hearing filter to filter spectrogram,then extracting speaker's characteristics through pulse coupled neural network(PCNN).Simulation results show that Euclidean distance of the speaker's entropy sequences through Gamma tone filter is shorter than that not through Gamma tone filter,which improves the recognition rate.
出处 《科学技术与工程》 2010年第30期7533-7535,7540,共4页 Science Technology and Engineering
关键词 GAMMA tone滤波器 PCNN 特征提取 Gamma tone filter PCNN feature extraction
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参考文献4

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共引文献6

同被引文献10

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