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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 14 | Issue 8 | Month- August 2026
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Paper Title
AI-Powered Spam Call Detection Using Speech-to-Text and NLP
Authors
Lakshmi K K, Shreeganesh Nayak, Sherwin J, Sahitya Prabhu, Shreya S Jain
Keywords
Spam call detection, speech-to-text, AWS Transcribe, Google Gemini API, natural language processing (NLP), call classification, JSON, automated spam filtering, AI-driven spam detection, real-time call analysis
Abstract
Spam calls have become a widespread nuisance, leading to wasted time, privacy concerns, and potential financial scams. To address this issue, we present Callnsight, an automated spam call detection system that leverages speech-to-text conversion and natural language processing. The system processes audio input from phone calls, converts it into text using AWS Transcribe, and analyzes the transcript using Google Gemini API to determine whether the call is spam. The API's output, structured in JSON format, enables easy extraction of relevant insights for classification. Callnsight provides a scalable and efficient approach to spam detection, offering real-time analysis and improving user security. This paper details the system architecture, implementation process, and potential improvements for enhancing spam detection accuracy.
IJCRT's Publication Details
Unique Identification Number - IJCRTBE02062
Paper ID - 289441
Page Number(s) - 470-476
Pubished in - Volume 13 | Issue 7 | July 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Lakshmi K K, Shreeganesh Nayak, Sherwin J, Sahitya Prabhu, Shreya S Jain, "AI-Powered Spam Call Detection Using Speech-to-Text and NLP", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 7, pp.470-476, July 2025, Available at :http://www.ijcrt.org/papers/IJCRTBE02062.pdf
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Volume 14 | Issue 8
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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