A Deep Learning System for Sentiment Analysis of Service Calls

Autor:	Jia, Yanan, SungChu, Sony
Rok vydání:	2020
Předmět:	Computer Science - Computation and Language
Druh dokumentu:	Working Paper
Popis:	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. Comment: 10 pages, 3 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2004.10320 Zobrazit plný text záznamu View this record from Arxiv