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SPEAKER-INDEPENDENT SPEECH RECOGNITION BASED ON FAST NEURAL NETWORK

机译:基于快速神经网络的说话人独立语音识别

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摘要

This paper presents a fast Neural Network algorithm, in which the step is regarded as the function of the error and the output function of network node, and weight is calculated by different step. By adopting the fast NN algorithm, we developed a speaker-independent speech recognition system. The experiment shows that the new algorithm is over 10 times faster than the traditional BP algorithm and has better performance and spreading ability.
机译:本文提出了一种快速的神经网络算法,该算法将步长作为误差的函数和网络节点的输出函数,并通过不同的步长计算权重。通过采用快速神经网络算法,我们开发了与说话者无关的语音识别系统。实验表明,新算法比传统的BP算法快10倍以上,并且具有更好的性能和扩展能力。

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