| 基于自适应子带功率谱熵的语音端点检测算法 |
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| 引用本文： | 李金宝,屈百达,徐宝国,周小祥.基于自适应子带功率谱熵的语音端点检测算法[J].计算机工程与应用,2007,43(12):57-58,65. |
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| 作者姓名： | 李金宝 屈百达 徐宝国 周小祥 |
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| 作者单位： | 江南大学,通信与控制工程学院,江苏,无锡,214122 |
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| 摘 要： | 在语音处理中,鲁棒性端点检测是语音处理最重要的领域之一,首先提出了一种子带功率谱熵(SPSE)的特征参数,然后,该参数结合Wuetal提出的自适应子带方法(ABS);发现了一种新颖的鲁棒特征参数-自适应子带谱熵(ASPSE),它能成功地在不同的背景噪声下检测语音端点。实验结果表明,在不同的噪声环境和信噪比下,ASPSE参数非常有效,而且该算法优于其它算法。
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| 关 键 词： | 自适应处理 端点检测 子带分析 功率谱熵 |
| 文章编号： | 1002-8331（2007）12-0057-02 |
| 修稿时间： | 2006-09 |
Speech endpoint detection algorithm based on adaptive subband power spectral entropy |
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| LI Jin-bao,QU Bai-da,XU Bao-guo,ZHOU Xiao-xiang.Speech endpoint detection algorithm based on adaptive subband power spectral entropy[J].Computer Engineering and Applications,2007,43(12):57-58,65. |
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| Authors: | LI Jin-bao QU Bai-da XU Bao-guo ZHOU Xiao-xiang |
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| Affiliation: | Communication and Control Academy, Southern Yangtze University, Wuxi,Jiangsu 214122, China |
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| Abstract: | In speech processing,robust endpoint detection is one of the most important areas of speech processing.The paper first proposes a feature parameter,called Subband Power Spectral Entropy(SPSE).This method is combined with the Adaptive Band Selection(ABS) method proposed by Wu et al.Finally,a novel robust feature parameter,Adaptive Subband Power Spectral Entropy(ASPSE),is presented to successfully detect endpoints in different background noises.Experimental results indicate that the ASPSE parameter is very effective under different noise conditions with several SNRs.Furthermore,the proposed algorithm outperforms other algorithms. |
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| Keywords: | adaptive processing endpoint detection subband analysis power spectral entropy |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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