MRI
MRI India Journals Vol. 14 No. 1 (2025)

AI Powered Voice Agent using NLP and ASR

Authors

  • S. O. Bagnawar
  • A. S. Rananavare
  • R. V. Rananavare
  • D. D. Tarange
  • R. D. Thombare

DOI:

https://doi.org/10.65521/ijaece.v14i1.797

Keywords:

Voice Agent Natural Language Processing (NLP) Automatic Speech Recog- nition (ASR) Call Center Automation Multilingual AI Large Language Models (LLMs) N8N.

Abstract

The demand for intelligent, automated communication systems has signifi- cantly increased with the growth of businesses and customer service requirements. Tra- ditional call centers require high manpower, leading to increased operational costs and inconsistent service quality. This paper surveys the development of AI-powered voice agents using Natural Language Processing (NLP) and Automatic Speech Recognition (ASR) for automating call center operations. The system supports Marathi, Hindi, and English, enabling multilingual communication and bridging the gap between technology and regional language users.

A key feature of this work is the integration of the N8N automation platform, which enables modular workflows for call handling, appointment booking, and marketing pro- cesses. By leveraging N8N, the system can seamlessly connect ASR, NLP, and Large Language Models (LLMs) such as ChatGPT and Gemini, ensuring flexibility, scalability, and ease of deployment. This modular approach reduces the complexity of development while allowing customization for businesses of different sizes.

We discuss the background, related works, methodologies, performance results from ex- isting studies, and future research directions. The survey highlights how voice-based AI agents, integrated with N8N and modern LLMs, can transform customer support, mar- keting, and appointment management by reducing human dependency and operational costs.

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Published

2025-11-08

How to Cite

Bagnawar, S. O., Rananavare, A. S., Rananavare, R. V., Tarange, D. D., & Thombare, R. D. (2025). AI Powered Voice Agent using NLP and ASR. International Journal on Advanced Electrical and Computer Engineering, 14(1), 245–247. https://doi.org/10.65521/ijaece.v14i1.797

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