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RBF神经网络用语语音识别, 自己写的程序!-RBF neural network language speech recognition, write their own procedures.
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小波神经网络用语孤立词语音识别,自己做的程序,-wavelet neural network terminology isolated Speech Recognition, their own procedures,
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一种简单有效的基于动态时变语音识别源码
对于大多数研究者来说,寻找能够匹配二重时间序列信号的最佳途径是很重要的,因为它有许多重要的应用需求.DTW是实现这项工作的显著技术,尤其在语音识别技术领域,在这里一个测试信号被按照参照模板拉伸或压缩,
,Searching for the best path that matches two time-series signals is the main task for many researchers, because of its importa
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用BP神经网络对孤立词语音识别Matlab语音仿真过程,BP neural network used for isolated word speech recognition voice Matlab simulation
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基于神经网络的语音识别技术研究
基于神经网络的语音识别技术研究-Neural Network Based Speech Recognition Technology based on neural network speech recognition technology research
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neural network speech recognition.
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基于模糊神经网络的语音识别,输入为测试变量,一直应该是神经网络的各个权值。-Based on fuzzy neural network speech recognition, input for the test variables, neural network should have all the right values.
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基于RBF神经网络的语音识别方法的应用研究-RBF neural network-based speech recognition methods applied research
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基于Mel倒谱特征和RBF网络的孤立词语音识别方法-Mel-based cepstral features and RBF networks isolated word speech recognition method
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Tutorial for speech recognition
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Using Radial Basis Probabilistic Neural Network for Speech Recognition
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Speech Recognition with TDNN(Time delay neural network)
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Automatic Speech Recognition with Neural Network
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speech recognision is used to develop automatic speech regonision system and also to normalise it and then map it to a particular user voice.
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基于人工神经网络的语音识别,运用了从语音中提取出的LPC参数与人工神经网络结合进行识别,使用matlab调试-Artificial neural network based speech recognition, the use of speech extracted from the LPC parameters and artificial neural network to identify, debug using matlab
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就目前三种主流的语音识别算法:动态时间规(DTW)、隐马尔科夫模型(HMM)和人工神经网络(ANN)。分析它们的原理、特点及实现过程,对 DTW 的语音识别进行实验,通过对比分析三种算法的特点,结合本文研究的实际情况,选择 DTW 作为研究的重点,提出利用遗传算法对其进行改进。
-The three mainstream speech recognition algorithms: Dynamic Time Regulations (DTW), hidden Markov model (HM
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基于带动量项的BP神经网络语音识别,可作为练习的参考-speech recognition based on BP neural network
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神经网络进行语音识别:/enframe.m,该函数将输入向量分为固定长度固定重叠量的帧。/SampleCreate.m,将取所有音频的mfcc系数处理成神经网络函数所需的输入格式-Neural networks for speech recognition
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使用hmm隐马尔科夫模型 进行语音识别,论文效果不错-Hmm using hidden Markov model for speech recognition
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程序中选取了民歌、古筝、摇滚和流行四类不同音乐 ,用 BP 神经网络实现对这四类音乐
的有效分类。(The program selected folk songs, zither, rock and popular four different music, with BP neural network to achieve the effective classification of these four types of music.)
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