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Integrated Design of Financial Self-Service Terminal Based on Artificial Intelligence Voice Interaction.

Huizhong Chen1, Shu Chen2, Jingfeng Zhao1

  • 1College of Economics and Management, Northwest University, Xi'an, China.

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This study integrates artificial intelligence (AI) voice interaction into financial self-service terminals, improving user experience and system performance. The AI-powered terminal demonstrates accurate voice recognition and efficient operation for daily financial tasks.

Keywords:
artificial intelligencefinancial self-helpintegrated designintelligent voiceterminal

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Area of Science:

  • Computer Science
  • Human-Computer Interaction
  • Artificial Intelligence

Background:

  • The rapid advancement of artificial intelligence (AI) and automation necessitates intelligent solutions in various sectors.
  • The financial industry, characterized by high growth potential, benefits from technological integration in self-service terminals.
  • Intelligent financial self-service terminals with enhanced user interaction are crucial for economic and technological development.

Purpose of the Study:

  • To design and develop an integrated financial self-service terminal incorporating AI-driven voice interaction.
  • To investigate the principles of AI-based voice interaction and its application in financial terminals.
  • To evaluate the performance, user experience, and accuracy of the developed voice-interactive terminal.

Main Methods:

  • Introduction to the concept and components of financial self-service terminal integration.
  • Study of AI-based voice interaction principles and design of an integrated terminal structure.
  • Empirical testing of voice interaction technology, user experience, and terminal performance.

Main Results:

  • Voice interaction delay estimation accuracy within five sampling points, confirming algorithm practicality.
  • Effective noise-robust endpoint detection using CO complexity for speech recognition.
  • Acceptable azimuth and direction angle errors (within a few degrees) for voice positioning.
  • Improved accuracy in intercepting effective speech signals via an enhanced algorithm.
  • Terminal exhibits short running/delay times, low memory/CPU usage, and over 80% speech recognition accuracy.

Conclusions:

  • The integrated AI voice interaction system is practical and meets the requirements for financial self-service terminals.
  • The developed terminal offers an efficient, user-friendly experience with robust voice recognition capabilities.
  • The study validates the effectiveness of AI voice interaction in enhancing financial self-service terminal functionality and user satisfaction.