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this Program utilized a new method
for generation codebook in Hidden Markov
Models (HMM). Hybrid HMM and neural
networks have been applied to improve
recognition in speech processing. -this Program utilized a new method
for generation
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从语音中提取出的LPC参数，并用人工神经网络进行语音识别-Extracted from the voice of the LPC parameters and artificial neural networks for speech recognition
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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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考虑雨衰 阴影 和多径影响，完整的基于HMM的语音识别系统，包括最小二乘法、SVM、神经网络、1_k近邻法。- Consider shadow rain attenuation and multipath effects Complete HMM-based speech recognition system, Including the least squares method, the SVM, neural networks, 1 _k neighbor method.
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实现典型相关分析，完整的基于HMM的语音识别系统，包括最小二乘法、SVM、神经网络、1_k近邻法。- Achieve canonical correlation analysis, Complete HMM-based speech recognition system, Including the least squares method, the SVM, neural networks, 1 _k neighbor method.
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