文件名称:simulator_for_DTW
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传统的DTW算法在进行孤立词语音识别时着重于时间规整和语音测度的计算 , 而没有
对数据的可靠性和有效性进行分析。本文提出了一种改进的端点检测算法 , 并采用一种改进的
DTW算法 , 在计算机上进行了仿真。实验结果表明采用改进后的DTW算法有效的降低了识别时
间和存储数据量 , 提高了系统性能-Traditional DTW algorithm in isolated word speech recognition when the focus on the time warping and voice measure of calculation, but not on the reliability and validity of data for analysis. This paper presents an improved endpoint detection algorithm, and using an improved DTW algorithm, the computer simulation. The experimental results show that the use of the improved DTW algorithm effectively reduces the recognition time and storage amount of data, improved system performance
对数据的可靠性和有效性进行分析。本文提出了一种改进的端点检测算法 , 并采用一种改进的
DTW算法 , 在计算机上进行了仿真。实验结果表明采用改进后的DTW算法有效的降低了识别时
间和存储数据量 , 提高了系统性能-Traditional DTW algorithm in isolated word speech recognition when the focus on the time warping and voice measure of calculation, but not on the reliability and validity of data for analysis. This paper presents an improved endpoint detection algorithm, and using an improved DTW algorithm, the computer simulation. The experimental results show that the use of the improved DTW algorithm effectively reduces the recognition time and storage amount of data, improved system performance
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基于DTW改进算法的孤立词识别系统的仿真与分析.pdf