Voice Recognition Trading System

• Author(s):

  Dr. A. Hemalatha | Anitha Mosses | Anushraj S | Balaji P

• Keywords:

• Abstract:

  Financial Trading Continues To Serve As A Cornerstone Of The Global Economy, Yet Traditional Trading Systems Remain Largely Optimized For Skilled Professionals And Rely Heavily On Manual Interfaces Such As Keyboards And Touch-based Inputs. These Interfaces Impose Accessibility Barriers For Novice Traders, Elderly Individuals, And Persons With Disabilities, Limiting Their Active Participation In Financial Markets. Recent Advancements In Artificial Intelligence (AI), Automatic Speech Recognition (ASR), And Natural Language Processing (NLP) Have Opened New Opportunities For Human-computer Interaction Through Natural Speech. Leveraging These Technologies, This Paper Presents Smart Voice Trade (SVT) — An Intelligent Voice-driven Trading Platform Designed To Execute Financial Transactions Through Spoken Commands In Real Time. The Proposed System Integrates A Multi-layered Architecture Combining ASR For Speech Transcription, NLP For Intent And Entity Extraction, And A Secure Broker API Interface For Order Placement And Validation. A Built-in Risk Verification Module Ensures Trade Integrity By Screening For Abnormal Parameters, Market Anomalies, And Execution Inconsistencies. The Platform Also Features Adaptive Speech Models Capable Of Handling Diverse Accents, Background Noise, And Variable Speech Rates, Enabling Robust Performance Across Heterogeneous User Environments. Experimental Evaluation Using A Dataset Of Over 5,000 Voice Samples Demonstrates An Average Intent Recognition Accuracy Of 95.8%, Precision Of 94.9%, And Average Latency Below 220 Milliseconds, Confirming Its Suitability For Real-time Trading Contexts. The System Not Only Enhances Efficiency And Inclusivity In Trading But Also Introduces A Scalable Foundation For AI-assisted Financial Decision-making. By Bridging The Gap Between Voice Interaction And Secure Trading Infrastructure, SVT Contributes To The Democratization Of Fintech Accessibility And Sets The Groundwork For Future Research On Autonomous, Conversational Trading Assistants.

---

Other Details

• Paper id:

  IJSARTV12I5105301

• Published in:

  Volume: 12 Issue: 5 May 2026

• Publication Date:

  2026-05-08

Download Article