语义情感分析沉浸式智能客厅模型研究  

Research on Immersive Intelligent Living Room Model Based on Semantic Sentiment Analysis

作　　者：孙东辉 张珣[1] SUN Dong-hui;ZHANG Xun(Institute of Modern Circuits and Intelligent Information,Hangzhou Dianzi University,Hangzhou 310018,China)

机构地区：[1]杭州电子科技大学现代电路与智能信息研究所,浙江杭州310018

出　　处：《软件导刊》2022年第6期49-56,共8页Software Guide

摘　　要：随着科技的迅猛发展,人们对家居的需求不断提高,在深度学习的渗透下,智能家居的发展迎来了新浪潮。现有智能家居系统大多根据用户具体指令进行相应操作,缺少对用户语义隐含的情感进行分析,也无法对用户行为作出预测。运用深度学习中自然语言处理领域的算法建立语义情感分析模型,使用LSTM-RNN网络学习分词后的语义文本特征向量,并引入注意力机制为语义词向量赋予不同的权重值,增强了特征训练,使客厅系统能够根据用户语音指示及挖掘用户情感信息作出自适应改变,从而让用户沉浸其中,体验更智能化的服务。With the rapid development of science and technology,people’s demand for home furnishing is constantly increasing.With the penetration of deep learning,the development of smart home ushered in a new wave.The existing smart home system mostly carries out the corresponding operation according to the specific instructions of the user,and lacks the analysis of the emotion implied by the user’s semantics,nor can it predict the user’s behavior.Therefore,algorithms in the field of natural language processing in deep learning are used to establish semantic sentiment analysis model,and LSTM-RNN network is used to learn semantic text feature vectors after word segmentation,and attention mechanism is introduced to assign different weight values to semantic word vectors,so as to enhance feature training.The living room system can be accompanied by the user’s voice instructions and mining the user’s emotional information to make adaptive changes,enabling users to immerse themselves and experience more intelligent services.

关 键 词：智能家居 语音识别 注意力机制 LSTM-RNN 情感分析 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]