AI-Based IVR

TL;DR

This paper explores integrating AI technologies like speech-to-text, LLM-based query classification, and speech synthesis into IVR systems, especially for Kazakh, to enhance efficiency and customer service in call centers.

Contribution

It presents a novel AI-based IVR system tailored for Kazakh, combining speech processing and language models, with practical implementation insights and demonstrated improvements.

Findings

Reduced operator workload in call centers

Improved customer service quality

Enhanced query processing efficiency

Abstract

The use of traditional IVR (Interactive Voice Response) methods often proves insufficient to meet customer needs. This article examines the application of artificial intelligence (AI) technologies to enhance the efficiency of IVR systems in call centers. A proposed approach is based on the integration of speech-to-text conversion solutions, text query classification using large language models (LLM), and speech synthesis. Special attention is given to adapting these technologies to work with the Kazakh language, including fine-tuning models on specialized datasets. The practical aspects of implementing the developed system in a real call center for query classification are described. The research results demonstrate that the application of AI technologies in call center IVR systems reduces operator workload, improves customer service quality, and increases the efficiency of query processing. The proposed approach can be adapted for use in call centers operating with various languages.