论文标题
深度学习系统，用于对服务电话的情感分析
A Deep Learning System for Sentiment Analysis of Service Calls
论文作者
论文摘要
情感分析对于人工智能（AI）的发展至关重要。情感理解可以帮助AI复制人类的语言和话语。研究训练有素的客户服务代表（CSR）的情感状态的形成和反应可以帮助使人与人工智能之间的互动更加聪明。在本文中，关于现实世界多方对话（即服务呼叫）首先进行了情感分析管道。基于从源信息中提取的声学和语言特征，建立了一种新颖的语音情感识别方法。调查了沟通过程中各方的情感模式，以及各方之间的互动情感模式。
Sentiment analysis is crucial for the advancement of artificial intelligence (AI). Sentiment understanding can help AI to replicate human language and discourse. Studying the formation and response of sentiment state from well-trained Customer Service Representatives (CSRs) can help make the interaction between humans and AI more intelligent. In this paper, a sentiment analysis pipeline is first carried out with respect to real-world multi-party conversations - that is, service calls. Based on the acoustic and linguistic features extracted from the source information, a novel aggregated method for voice sentiment recognition framework is built. Each party's sentiment pattern during the communication is investigated along with the interaction sentiment pattern between all parties.
