International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 06 | Jun 2025
p-ISSN: 2395-0072
www.irjet.net
SynKron AI: A conversational, voice-based & IoT assistant Aditya Saxena1, Leena Patel2, Aman Dixit3, P.Anirudha Varma4, Mr. Nilesh Gupta5, Dr. Shanu K Rakesh6 1,2,3,4 -B.TECH Scholar , Chouksey Engineering College , Bilaspur 5–Assistant Professor , Chouksey Engineering College , Bilaspur
6–Head of Department C.S.E. , Chouksey Engineering College , Bilaspur
Department of Computer Science & Engineering ---------------------------------------------------------------------***--------------------------------------------------------------------more possibilities of control and offline functionality ABSTRACT- The proposed paper presents SynKron AI, a compared to common commercial offerings.
conversational, voice-based assistant framework that combines intelligent automation and a graphical user interface (GUI) to make human-machine interaction easy. SynKron AI is based on Python backend and PyQt5 front end and integrates speech recognition, natural language processing, and on-the-fly automation. This system has voice control, real time web search, image generation module, media playback and smart system management. SynKron is made to operate with both local and cloud-based components and is optimized to be used both personally and industrially, as well as to integrate with IoT. The modularity, scalability, and privacy-by-design of the platform makes it a feasible solution to smart environments.
1.2 Problem Statement: Platform dependencies and a limited desktop integration capability wherein modern virtual assistants such as Siri, Alexa, and Google Assistant are concerned, tend to hamper these assistants and make them less useful when it comes to more advanced automation and customization. An open, extensible, intelligent desktop-based assistant that can do real-time search, automate tasks, control application, and interact via voice and natural language is required. SynKron AI fills this gap with a modular, Python powered desktop assistant, which features a natural voice and GUI based interaction, real time web availability, automation and media control, optimized to maximize user productivity.
1. INTRODUCTION The demand of smart and customizable systems is increasing with the intensification of technology in everyday lives. Though platform restrictions are something to reckon with, popular assistants such as Siri and Alexa can only be convenient. SynKron AI fills this gap with a modular, Pythonbased voice assistant, focused on desktops. It is a combination of real-time web search, automation, and interactive PyQt5 GUI with voice recognition and AI response generation. It has an open-source design, which targets personal and educational uses and internet of things (IoT)oriented applications.
1.3 Objectives: • Create an artificially intelligent assistant which will be controlled by voice or text messages. • Introduce web search, playback of media content in real-time, and automation of apps. • Integrate API to generate images on demand. • Implement PyQt5 GUI that is easy to use.
2. LITERATURE SURVEY
1.1 Background: The newer AI developments have enhanced the interaction between people and computers by using voice-activated assistants to make tasks such as media playback, information retrieval, and automation easier. Nevertheless, widely-used assistants such as Siri or Alexa are dependent on the cloud and can barely be customized or integrated into the desktop. In order to overcome such problems SynKron AI was created as an open-source and versatile assistant which is mainly applied in Python. It is speech recognition, text-to-speech, real time search, image generation and GUI automation all integrated into a single modular platform. SynKron can be easily customized and integrated with other systems (home automation or industrial IoT) and provides the user with
© 2025, IRJET
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Impact Factor value: 8.315
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I.
IEEE Spectrum (2023): mentioned the shortcomings of voice assistants when used in an offline or crossplatform setting and referred to the importance of open-source modularity. [Ref-[1]]
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ACM Digital Library (2024): checked the incorporation of smart modules such as NLP, image generation, and automation in AI assistants. [Ref-[2]]
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Elsevier Journal on Human-Centric Computing (2023): Analysed the user behaviour and the role of the contextual memory in assistants. [Ref-[3]]
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