From Data to Decisions: Integrating Speech Analytics and Machine Learning in Call Centers using AI tools

Ruxsoraxon Abduqayumova^1,2,*, Nargiza Alimukhamedova², Maxbuba Ismailova³

¹Central Asian University in Tashkent, Uzbekistan

²Westminster International University in Tashkent, Uzbekistan

³Department of Financial Analysis and Audit, Tashkent State University of Economics, Uzbekistan

Emails: r.abduqayumova@centralasian.uz; m.ismoilova@tsue.uz; nalimukhamedova@wiut.uz

Abstract

The current swift advancement of Artificial Intelligence (AI) technologies is transforming operations management by integrating real-time data-driven insights for cost optimization and improved decision-making. In this paper, we explore the fusion of artificial intelligence (AI) technologies in call center operations management, focusing on how the integration of speech-to-text, text-to-speech, and speech analytics tools is revolutionizing customer interaction and decision-making. The fusion of real-time conversational data with advanced machine learning algorithms enables organizations to extract actionable insights, optimize key performance indicators (KPIs), and enhance customer satisfaction. Furthermore, in this research, we are estimating the approximate return on investment in the benchmarked private sectors of Uzbekistan, thus contributing to the future networks in the industry. Our research work bridges the gap between theoretical AI advancements and their practical applications, contributing to the growing body of knowledge on information fusion in intelligent systems in the emerging Uzbek market.

Keywords: Artificial Intelligence; Future Networks; Speech-to-Text and Text-to-Speech; Call Analytics; ROI