频率估计算法的普遍问题是计算量大并且在低信噪比时性能较差.文中提出一种基于逆积分方程(Inversion Integral Equation,IIE)的频率估计新算法.首先利用快速傅立叶变换得到频率的粗估计,并从傅立叶变换中提出一个窄带信号建立积分方程.然后通过对积分方程中参数和特征频率的估计得到最终的频率估计.仿真结果显示文中算法以适中的计算量在低信噪比下达到了较好的性能.
In the traditional multi-stream fusion methods of speech recognition, all the feature components in a data stream share the same stream weight, while their distortion levels are usually different when the speech recognizer works in noisy environments. To overcome this limitation of the traditional multi-stream frameworks, the current study proposes a new stream fusion method that weights not only the stream outputs, but also the output probabilities of feature components. How the stream and feature component weights in the new fusion method affect the decision is analyzed and two stream fusion schemes based on the mariginalisation and soft decision models in the missing data techniques are proposed. Experimental results on the hybrid sub-band multi-stream speech recognizer show that the proposed schemes can adjust the stream influences on the decision adaptively and outperform the traditional multi-stream methods in various noisy environments.
