基于神经网络的AVS-P10开环模式选择算法优化  

Optimization of AVS-P10 Open-loop Mode Selection Algorithm Based on Neural Network

作　　者：崔佰会 高戈[1] 姜林[1,2] CUI Baihui;GAO Ge;JIANG Lin(National Engineering Research Center for Multimedia Software,Wuhan University,Wuhan 430072,China;Software College,East China University of Technology,Nanchang 330013,China)

机构地区：[1]武汉大学国家多媒体软件工程技术研究中心,武汉430072 [2]东华理工大学软件学院,南昌330013

出　　处：《计算机工程》2018年第9期256-262,共7页Computer Engineering

基　　金：国家自然科学基金"基于上下文相关的音频非盲带宽扩展编码研究"(61762005)

摘　　要：现有的开环模式选择算法依赖信号分类的准确率,但多数情况下准确率较低,造成开环模式下编码音质较差。为此,提出一种改进的基于神经网络的开环模式选择算法。使用神经网络替换原开环模式选择的决策树算法,拟合闭环模式选择结果进行训练得到模式选择分类器,按照闭环模式选择的逻辑过程,运用神经网络预测输入的信号,在ACELP256和TVC256两种编码模式的信噪比取代编码尝试计算得到的信噪比。实验结果表明,与原AVS-P10开环选择方法相比,提出的2种模式在语音分类准确率上分别提升5.96%和18.07%,在音乐分类准确率上分别提升3.84%和20.29%,其主客观编码音质评测明显提升。The existing open-loop mode selection algorithm relies on the accuracy of signal classification,but in most cases the accuracy is low,resulting in poor coding quality in open-loop mode.Therefore an improved neural network based open-loop mode selection algorithm is proposed.The decision tree algorithm of the original open-loop mode selection is replaced by the neural network,and the closed-loop mode selection is selected for training to obtain the mode selection classifier.According to the logic process of the closed-loop mode selection,the neural network is used to predict the input signal,and the two codes are ACELP256 and TVC256.The signal to noise ratio of the mode replaces the signal-to-noise ratio that the coding attempt is calculated.Experimental results show that the accuracy of the two methods is 5.96%and 18.07%,respectively,and the accuracy of music classification is 3.84%and 20.29%,the performance of subjective and objective tone has high improvement.

关 键 词：神经网络 先进音视频编码 模式选择 特征选择 信号分类 信噪比估计 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]