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A Critical Analysis of the Emotive Content in Customer Speech for a Robust CRM
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Author(s): Sippee Bharadwaj (International School of Business and Research, Bangalore, India), Nila Chotai (International School of Business and Research, Bangalore, India), Manish Kothari (International School of Business and Research, Bangalore, India)and Chinmoy Bharadwaj (University of Science and Technology, Meghalaya, India)
Copyright: 2025
Pages: 36
Source title:
Demystifying Emotion AI, Robotics AI, and Sentiment Analysis in Customer Relationship Management
Source Author(s)/Editor(s): Fazla Rabby (Stanford Institute of Management and Technology, Australia), Nasim Ahmed (The University of Sydney, Australia), Amandeep Sehmi (Canterbury Institute of Management, Australia), Rohit Bansal (Rockford College, Sydney, Australia)and Nishita Pruthi (Asian School of Business, India)
DOI: 10.4018/979-8-3373-1867-7.ch012
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Abstract
Emotion analysis plays a vital role in Customer Relationship Management (CRM), impacting customer interactions and brand perception. While previous CRM systems have relied mostly on text-based sentiment analysis, the expanding usage of audio-based feedback underlines the necessity for speech-based emotion recognition. This research analyses vowel prosodic qualities in customer speech to better emotion prediction, boost customer retention, and expedite corporate procedures. By concentrating on vowel-level emotion extraction, this study intends to boost the accuracy and reliability of emotion classifiers via an analysis of consumer audio feedback from online purchase platforms. Advanced speech analytics approaches are applied to decipher the emotional content of utterances by studying prosodic variables such as F0, MFCC, ZCR, STE, and formants. The results contribute to translating sentiment research into practical CRM solutions, developing customer-centric business strategies, and boosting the usefulness of business analytics.
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