| 多重分形维数在语音分割和语音识别中的应用 |
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| 引用本文： | 董远,胡光锐.多重分形维数在语音分割和语音识别中的应用[J].上海交通大学学报,1999,33(11):1406-1408. |
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| 作者姓名： | 董远 胡光锐 |
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| 作者单位： | 上海交通大学电子工程系上海200030 |
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| 摘 要： | 语音气流中具有混沌特征，而分形可以定量地分析混沌现象，故分形可作为分析语音信号的数学工具．由于传统的Ｈａｕｓｄｏｒｆｆ－Ｂｅｓｉｃｏｖｉｔｃｈ 维数没有考虑关于集合中点的分布信息，本文引入多重分形维数来克服上述缺点．实验表明，多重分形维数语音分割方法明显好于单一Ｈａｕｓｄｏｒｆｆ－Ｂｅｓｉｃｏｖｉｔｃｈ 分形维数的语音分割方法
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| 关 键 词： | 分形 多重分形 语音分割 语音识别 |
| 文章编号： | 1006-2467(1999)11-1406-03 |
| 修稿时间： | 1998年11月25 |
Application of Multifractal Dimension in Speech Segmentation and Recognition |
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| DONG Yuan,HU Guang rui Dept. of Electronic Eng.,Shanghai Jiaotong Univ.,Shanghai ,China.Application of Multifractal Dimension in Speech Segmentation and Recognition[J].Journal of Shanghai Jiaotong University,1999,33(11):1406-1408. |
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| Authors: | DONG Yuan HU Guang rui Dept of Electronic Eng Shanghai Jiaotong Univ Shanghai China |
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| Institution: | DONG Yuan,HU Guang rui Dept. of Electronic Eng.,Shanghai Jiaotong Univ.,Shanghai 200030,China |
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| Abstract: | There are chaotic characters in speech air flow. And fractal can be used to quantify the chaotic phenomenon. So we can use fractal as a mathematical vehicle to analyze speech signals. The traditional Hausdorff Besicovitch dimension does not consider the information about the distribution of the points in the set. Here we introduced multifractal dimension to overcome the drawback. The experiment result shows better segmentation is achieved by multifractal dimension than only by single Hausdorff Besicovitch fractal dimension. |
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| Keywords: | fractal multifractal speech segmentation speech recognition |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
