针对低信噪比条件下语音端点检测精度受噪声干扰严重的问题,提出了一种基于投影分类的语音端点检测方法。该方法首先利用长时语音信号变化率测度特征进行低信噪比环境中的语音特征计算,充分利用语音信号和非语音信号的不同来增强低信噪...针对低信噪比条件下语音端点检测精度受噪声干扰严重的问题,提出了一种基于投影分类的语音端点检测方法。该方法首先利用长时语音信号变化率测度特征进行低信噪比环境中的语音特征计算,充分利用语音信号和非语音信号的不同来增强低信噪比条件下的区分度;接着,采用Fisher准则对语音和背景噪声进行分类识别,确保投影后的特征参数类内散度最小、类间散度最大。实验结果表明,方法具有较高的检测精度,在信噪比为-10 d B的白噪声干扰情况下仍然保持了86.7%以上的正确检测率。展开更多
The indicators of flood damage assessment in the flood classification are often incompatible, and it is very difficult to use those indicators value directly for classification assessment. Projection pursuit technolog...The indicators of flood damage assessment in the flood classification are often incompatible, and it is very difficult to use those indicators value directly for classification assessment. Projection pursuit technology can project higher dimensional incompatible data into lower dimensional sub-space, and find the projection values for optimal projection index function to get the higher dimensional data structure features, which has been improved to be reasonable and effective for flood disaster classification assessment. However, it is a bit difficult to optimize the parameters of projection index functions, as a result, that limits the applications of this method. As an emerging heuristic global optimization algorithm based on swarm intelligence, particle swarm optimization algorithm has the ability of solving complex optimization problem, but it still be easily convergent early, and can not search the global optimal solution. In this paper, a flood disaster classification assessment method based on multi-swarm cooperative particle swarm optimization is proposed, which adopts a tri-parameter Logistic curve to construct the flood disaster projection pursuit model, and uses mul-ti-swarm system particle swarm optimization method to optimize the parameters of the projection index functions. The typical test function experiment shows that this optimization method can solve the early convergence commonly found in standard particle swarm optimization algorithm, which global optimized ability is improved greatly. Applied in flood disaster assessment in HeNan Province, the results using this method comparing with others indicates that it can assess effectively the flood disaster, and has better assessment accuracy and disaster resolution.展开更多
文摘针对低信噪比条件下语音端点检测精度受噪声干扰严重的问题,提出了一种基于投影分类的语音端点检测方法。该方法首先利用长时语音信号变化率测度特征进行低信噪比环境中的语音特征计算,充分利用语音信号和非语音信号的不同来增强低信噪比条件下的区分度;接着,采用Fisher准则对语音和背景噪声进行分类识别,确保投影后的特征参数类内散度最小、类间散度最大。实验结果表明,方法具有较高的检测精度,在信噪比为-10 d B的白噪声干扰情况下仍然保持了86.7%以上的正确检测率。
文摘The indicators of flood damage assessment in the flood classification are often incompatible, and it is very difficult to use those indicators value directly for classification assessment. Projection pursuit technology can project higher dimensional incompatible data into lower dimensional sub-space, and find the projection values for optimal projection index function to get the higher dimensional data structure features, which has been improved to be reasonable and effective for flood disaster classification assessment. However, it is a bit difficult to optimize the parameters of projection index functions, as a result, that limits the applications of this method. As an emerging heuristic global optimization algorithm based on swarm intelligence, particle swarm optimization algorithm has the ability of solving complex optimization problem, but it still be easily convergent early, and can not search the global optimal solution. In this paper, a flood disaster classification assessment method based on multi-swarm cooperative particle swarm optimization is proposed, which adopts a tri-parameter Logistic curve to construct the flood disaster projection pursuit model, and uses mul-ti-swarm system particle swarm optimization method to optimize the parameters of the projection index functions. The typical test function experiment shows that this optimization method can solve the early convergence commonly found in standard particle swarm optimization algorithm, which global optimized ability is improved greatly. Applied in flood disaster assessment in HeNan Province, the results using this method comparing with others indicates that it can assess effectively the flood disaster, and has better assessment accuracy and disaster resolution.
