This paper describes the use of multi-layer perception model of neural network in speech recognition.
本文研究神经网络的多层感知器模型在语音识别中的应用。
A new algorithm of employing the fuzzy neural network is proposed to realize speech data fusion for speech recognition under high noisy condition.
针对高噪音环境中的语音识别问题，提出一种利用模糊神经网络进行语音数据融合的新算法。
The mining techniques which use artificial neural network to solve the speech recognition for Deaf - mutes is given.
提出了一种基于人工神经网络的聋儿语音训练识别的多媒体特征挖掘技术。
Through using RBF neural network, speech recognition of isolated words is carried on.
识别网络使用RBF神经网络，进行了孤立词语音识别。
The paper has conducted the research focusing on speech emotion recognition based on BP neural network.
论文重点研究了基于BP神经网络的语音情感识别。
In the process of speech and speaker recognition with BP neural network, nearly several hundreds of input nodes are required, that lead a very large network scale and a very slow train speed.
在用BP网进行语音和说话人识别过程中，BP网的输入节点数一般在几百个左右，使得网络的规模过大，训练速度过慢。
The improvement scheme of traditional BP neural network in speech recognition is mainly studied.
主要研究了传统BP神经网络在实际语音识别中的改进方案。
Neural network are used to recognize the four basic human emotions including anger, happiness, sadness and fear in speech, and we achieve an average recognition rate of approximately 52.6%.
然后利用神经网络识别汉语语音中的四类基本情感(愤怒、高兴、悲伤和害怕)，取得了52.6%的平均识别率。
Based on the new neural network, a Chinese speech recognition system is established and has achieved high performance in experiments.
最后介绍了根据这一模型所设计的一个汉语语音识别系统，试验表明该网络在汉语语音识别方面具有较大的潜力。
Based on the new neural network, a Chinese speech recognition system is established and has achieved high performance in experiments.
最后介绍了根据这一模型所设计的一个汉语语音识别系统，试验表明该网络在汉语语音识别方面具有较大的潜力。
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