基于AlexNet模型的佤语语谱图识别  

Spectrum recognition of the Wa language based on the AlexNet model

作　　者：王翠 王璐 解雪琴 和丽华 潘文林[1] WANG Cui;WANG Lu;XIE Xue-qin;HE Li-hua;PAN Wen-lin(School of Mathematics and Computer Science, Yunnan Minzu University, Kunming 650500, China)

机构地区：[1]云南民族大学数学与计算机科学学院

出　　处：《云南民族大学学报（自然科学版）》2019年第4期377-381,共5页Journal of Yunnan Minzu University:Natural Sciences Edition

基　　金：国家自然科学基金(61363022);云南民族大学研究生创新基金(2018YJCXS227)

摘　　要：针对佤语语谱图的识别无需考虑清、浊音的影响这一特征.利用傅里叶变换将佤语转换为对应的语谱图信息,将深度卷积神经网络的AlexNet模型用于佤语语谱图识别.实验表明,语谱图识别可以有效解决语音识别过程中清、浊音对实验识别结果的干扰,实验准确率达到96%.Since it is unnecessary to consider the influence of clear and voiced sounds in the recognition of the Wa longuage spectrogram,this research uses the Fourier transform to transform the Wa language into the corresponding spectrum-related information.In addition,the AlexNet model of the deep convolutional neural network is introduced into the spectrum-based recognition of the Wa language.The result shows that the spectrum-based recognition of the Wa language can effectively solve the interference of clear and voiced speech in the process of speech recognition,and the experimental accuracy rate reaches 96%.

关 键 词：卷积神经网络(CNN) AlexNet模型 语谱图 佤语语谱图识别 

分 类 号：TN912.34[电子电信—通信与信息系统]