Patent Analysis of "Method and System for Analyzing Customer Calls by Implementing a Machine Learning Model to Identify Emotions" (US 11,630,999 B2): A Technological, Strategic, and Commercial Evaluation

Abstract

Purpose: To systematically analyze the patent "Method and System for Analyzing Customer Calls by Implementing a Machine Learning Model to Identify Emotions" (US 11,630,999 B2) and evaluate its technological innovation, strategic significance, and commercial potential in the field of artificial intelligence. The study examines how the patented invention identifies customer emotions from voice signals during support calls and enables customized, emotion-aware customer support.

Methodology: This study adopts an exploratory qualitative research approach based on the analysis of the selected patent. Relevant information was collected from publicly available sources, including Google Patents, Google Scholar, research publications, and other authentic online resources. SWOC Analysis and ABCDEF Analysis were applied to evaluate the patent's technological capabilities, commercial value, implementation challenges, and future opportunities.

Results & Analysis: The analysis shows that the patent introduces a machine-learning-based framework for identifying customer emotions from voice audio in support calls by extracting acoustic features and classifying emotional states using a trained neural network model. The invention has significant applications in customer experience management, contact-centre operations, telecommunications, banking and financial services, fraud detection, and mental-health-aware customer interaction. The study also identifies challenges related to linguistic and cultural variation in emotional expression, real-time processing demands, data privacy, and the subjectivity of emotion labelling.

Originality & Values: The study provides a comprehensive evaluation of the patent using structured analytical frameworks and highlights its technological, commercial, and societal significance. It demonstrates the patent's contribution toward strengthening emotionally responsive customer service, promoting responsible artificial intelligence, and supporting future advancements in affective computing and customer relationship management.

Type of Paper: Case Study-based Exploratory Research.