基于加权划分非平衡决策树的诗歌朗读情感度分析  

Analysis of Emotional Degree of Poetry Reading Based on WDOUDT

作　　者：董本清[1] 李凤坤 DONG Ben-qing;LI Feng-kun(Dalian Neusoft University of Information,Dalian,Liaoning 116023,China)

机构地区：[1]大连东软信息学院,辽宁大连116023

出　　处：《计算机科学》2020年第S02期46-51,共6页Computer Science

基　　金：辽宁省博士启动基金(20170520398);辽宁省教育厅科学技术一般项目(L2015041)。

摘　　要：本文面向诗歌朗读的情感度分析,提出了一种新的非平衡决策树算法。该算法称为加权划分非平衡决策树(Weighted Division of Unbalanced Decision Tree,WDOUDT),通过对诗歌朗读感染力的指标展开研究,从朗读的音频中提取梅尔频率倒谱系数,应用可解释性最强的决策树方法进行建模。加权划分非平衡决策树推导算法不使用进化算法和启发信息搜索,应用在诗歌朗读音频的情感度打分中,时间复杂度低于传统决策树,该算法具有更少的节点数和较好的泛化能力,对噪音数据有较好的鲁棒性。In this paper,a new unbalanced decision tree algorithm for infectious expressions of reading poem is proposed.This algorithm called Weighted Division of Unbalanced Decision Tree(WDOUDT).Through the study on the index of poetry reading appeal,mel-frequency cepstral coefficients are extracted from the reading audio,and the decision tree method with the strongest interpretability is used for modelling.WDOUDT does not use evolutionary algorithm and heuristic information search,it is applied to the emotional scoring of poetry reading audio,and the time complexity is lower than the traditional decision tree.The proposed algorithm has fewer nodes and better generalization ability,and has better robustness to noise data.

关 键 词：非平衡决策树 加权划分 情感度分析 快速收敛 

分 类 号：TP391.43[自动化与计算机技术—计算机应用技术]