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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: May 2026
Volume 11 | Issue 5
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Impact Factor : 8.14
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Issue Published : 120
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| Paper Title: | Multilingual Low-Latency AI Voice Agent for Automated Telephonic Interactions in Education and Healthcare |
| Authors Name: | Aleena B , Dr. Narayana Swamy Ramaiah |
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| Author Reg. ID: |
IJRTI_211966
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| Published Paper Id: | IJRTI2604278 |
| Published In: | Volume 11 Issue 4, April-2026 |
| DOI: | |
| Abstract: | Efficient telephonic communication remains a critical operational requirement in both educational institutions and healthcare systems, where high volumes of routine interactions such as appointment scheduling, enquiry handling, and follow-up notifications are common. Traditional communication methods, including manual calling and rule-based Interactive Voice Response (IVR) systems, often suffer from inefficiency, rigidity, and lack of contextual understanding. This paper presents a low-latency multilingual AI voice agent designed to enable real time, human-like telephonic interactions. The proposed system integrates Automatic Speech Recognition (ASR), Large Language Model (LLM)- driven dialogue management, and Text-to-Speech (TTS) within a unified pipeline optimized for minimal response delay. A key contribution is the incorporation of an uncertainty-aware dialogue orchestrator, which improves reliability by dynamically handling ambiguous inputs through clarification or escalation mechanisms. Additionally, the system supports multilingual communication with code-switching capabilities, making it suitable for linguistically diverse environments. A goal-oriented conversational framework ensures efficient task completion, while secure telephony integration enables seamless deployment in real-world scenarios. Experimental evaluation demonstrates reduced latency (~500 ms), high task completion rates (>90%), and improved user satisfaction, highlighting the system’s effectiveness in automating telephonic workflows in sensitive domains. |
| Keywords: | Multilingual AI, Voice Agent, ASR, LLM, TTS, Telephony Automation, Low Latency, Conversational AI. |
| Cite Article: | "Multilingual Low-Latency AI Voice Agent for Automated Telephonic Interactions in Education and Healthcare", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.c34-c37, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604278.pdf |
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| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2604278
Registration ID:211966
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: c34-c37 Country: Bangalore, Karnataka, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604278 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604278 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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