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Sentiment analysis is crucial for the advancement of artificial intelligence(AI). Sentiment understanding can help AI to replicate human language anddiscourse. Studying the formation and response of sentiment state fromwell-trained Customer Service Representatives (CSRs) can help make theinteraction between humans and AI more intelligent. In this paper, a sentimentanalysis pipeline is first carried out with respect to real-world multi-partyconversations - that is, service calls. Based on the acoustic and linguisticfeatures extracted from the source information, a novel aggregated method forvoice sentiment recognition framework is built. Each party's sentiment patternduring the communication is investigated along with the interaction sentimentpattern between all parties.

A Deep Learning System for Sentiment Analysis of Service Calls