Prototype of a Virtual Assistant System Integrated with AI

Rifky Lana Rahardian; I Putu Gede Abdi Sudiatmika; Komang Hari Santhi Dewi

doi:10.69693/jesa.v1i2.7

Authors

Rifky Lana Rahardian Institut Teknologi Dan Bisnis STIKOM Bali
I Putu Gede Abdi Sudiatmika Institut Teknologi dan Bisnis STIKOM Bali, Indonesia
Komang Hari Santhi Dewi Institut Teknologi dan Bisnis STIKOM Bali, Indonesia

DOI:

https://doi.org/10.69693/jesa.v1i2.7

Keywords:

Artificial Intelligence, Virtual Assistant, Information Technology

Abstract

This research focuses on the development of a prototype virtual assistant system integrated with artificial intelligence (AI) using the Rational Unified Process (RUP) method. The system is designed to improve user flexibility and efficiency by allowing interaction through voice commands, removing the need for traditional input devices. Python was selected as the primary programming language due to its robust capabilities in handling AI-driven applications. The system utilizes Whisper API for speech recognition, enabling the virtual assistant to accurately interpret voice inputs. Additionally, the integration of Chat GPT API allows the assistant to process and generate responses in a natural, context-aware manner. The combination of these technologies is expected to enhance user experience by making the system more intuitive and seamless, applicable to both daily tasks and complex business environments. The RUP method, structured into phases such as inception, elaboration, construction, and transition, was applied to ensure that the development process was iterative, flexible, and aligned with user needs. The results indicate that the integration of Whisper API with Chat GPT API significantly improves the quality and accuracy of voice-based interaction, streamlining system operation while minimizing the need for complex graphical interfaces. This research demonstrates the potential of voice-driven AI systems in increasing overall operational efficiency.

Downloads

Download data is not yet available.

References

Radziwill, N. M., & Benton, M. C. (2017). Evaluating quality of chatbots and intelligent conversational agents. Journal of Quality Management, 10(3), 23-39.

McTear, M., Callejas, Z., & Griol, D. (2016). The conversational interface: Talking to smart devices. Springer.

Haider, A., & Nisar, Q. A. (2020). AI-based virtual assistants and their impact on user experience in business settings. International Journal of Human-Computer Interaction, 36(7), 601-610.

Su, Y. (2019). Whisper AI for real-time voice-to-text transcription: A comparative study. IEEE Transactions on Multimedia, 22(4), 1030-1043.

Chen, C., & Li, P. (2021). Optimizing conversational AI using OpenAI's GPT-3 and Whisper API. Journal of Intelligent Systems, 30(1), 95-106.

Kaur, H., & Kumar, R. (2021). Applications of Python in AI development: A case study on chatbot implementations. Journal of Artificial Intelligence Research, 55, 89-112.

Zhang, Y., & Wu, Z. (2020). Enhancing virtual assistants using multi-modal machine learning. IEEE Access, 8, 174732-174744.

Hernandez, A., & Cruz, L. (2019). Whisper API for speech-to-text integration in mobile applications. Journal of Mobile Computing, 35(5), 450-467.

King, J., & Black, P. (2020). Performance evaluation of the GPT-3 model in customer service chatbots. Journal of Service Research, 23(2), 178-196.

Wu, J., & Wang, T. (2018). Intelligent systems: ChatGPT’s architecture and capabilities in automation. Journal of Software Engineering and Applications, 11, 123-139.

Park, S., & Lee, D. (2019). Voice recognition in AI-powered personal assistants. IEEE Transactions on Neural Networks and Learning Systems, 31(7), 1742-1755.

Tanaka, T., & Okamoto, M. (2021). Comparative analysis of AI-based virtual assistants. Journal of Information Technology Research, 14(3), 145-158.

Patil, P., & Gupta, R. (2022). Python and AI: A framework for developing interactive assistants using Whisper API. Journal of Computational Intelligence, 58(9), 1137-1150.

Lang, T., & Song, W. (2020). ChatGPT API in enhancing conversational flows in customer service applications. Journal of Human-Computer Studies, 137, 123-137.

Carver, J. & Price, A. (2022). Integration of voice and text-based AI in customer support systems. Journal of Applied Computing and Information Technology, 30(5), 654-662.

Silva, F., & Johnson, M. (2023). Whisper API: Use cases in developing multi-lingual transcription services. International Journal of Speech Technology, 26(2), 219-235.

Song, Y., & Li, M. (2022). Virtual assistants in the age of AI: Examining the role of Whisper API and ChatGPT in streamlining tasks. Artificial Intelligence Review, 55(3), 345-364.