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Artificial Intelligence and Virtual Assistant—Working Model
- Conference paper
- First Online: 29 September 2020
- Cite this conference paper
- Shakti Arora 13 ,
- Vijay Anant Athavale 13 ,
- Himanshu Maggu 13 &
- Abhay Agarwal 13
Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 140))
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6 Citations
In twenty-first-century virtual assistant is playing a very crucial role in day to day activities of human. According to the survey report of Clutch in 2019, 27% of the people are using the AI-powered virtual assistant such as: Google Assistant, Amazon Alexa, Cortana, Apple Siri, etc., for performing a simple task, people are using virtual assistant designed with natural language processing. In this research paper, we have studied and analyzed the working model and the efficiency of different virtual assistants available in the market. We also designed an intelligent virtual assistant that could be integrated with Google virtual services and work with the Google virtual assistant interface. A comparative analysis of the traffic and message communication with length of conversation for approximately three days is taken as input to calculate the efficiency of the designed virtual assistant.
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Panipat Institute of Engineering & Technology, Samalkha, Panipat, 132102, India
Shakti Arora, Vijay Anant Athavale, Himanshu Maggu & Abhay Agarwal
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Correspondence to Shakti Arora .
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Department of Electronics and Communication Engineering, University Institute of Engineering and Technology (UIET), Kurukshetra University, Kurukshetra, Haryana, India
Nikhil Marriwala
University Institute of Engineering and Technology (UIET), Kurukshetra University, Kurukshetra, Haryana, India
C. C. Tripathi
Department of Electrical and Computer System Engineering, RMIT University, Melbourne, VIC, Australia
Dinesh Kumar
Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Waknaghat, Himachal Pradesh, India
Shruti Jain
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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Arora, S., Athavale, V.A., Himanshu Maggu, Agarwal, A. (2021). Artificial Intelligence and Virtual Assistant—Working Model. In: Marriwala, N., Tripathi, C.C., Kumar, D., Jain, S. (eds) Mobile Radio Communications and 5G Networks. Lecture Notes in Networks and Systems, vol 140. Springer, Singapore. https://doi.org/10.1007/978-981-15-7130-5_12
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DOI : https://doi.org/10.1007/978-981-15-7130-5_12
Published : 29 September 2020
Publisher Name : Springer, Singapore
Print ISBN : 978-981-15-7129-9
Online ISBN : 978-981-15-7130-5
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Computer Science > Human-Computer Interaction
Title: gptvoicetasker: llm-powered virtual assistant for smartphone.
Abstract: Virtual assistants have the potential to play an important role in helping users achieves different tasks. However, these systems face challenges in their real-world usability, characterized by inefficiency and struggles in grasping user intentions. Leveraging recent advances in Large Language Models (LLMs), we introduce GptVoiceTasker, a virtual assistant poised to enhance user experiences and task efficiency on mobile devices. GptVoiceTasker excels at intelligently deciphering user commands and executing relevant device interactions to streamline task completion. The system continually learns from historical user commands to automate subsequent usages, further enhancing execution efficiency. Our experiments affirm GptVoiceTasker's exceptional command interpretation abilities and the precision of its task automation module. In our user study, GptVoiceTasker boosted task efficiency in real-world scenarios by 34.85%, accompanied by positive participant feedback. We made GptVoiceTasker open-source, inviting further research into LLMs utilization for diverse tasks through prompt engineering and leveraging user usage data to improve efficiency.
| Subjects: | Human-Computer Interaction (cs.HC) |
| Cite as: | [cs.HC] |
| (or [cs.HC] for this version) | |
| Focus to learn more arXiv-issued DOI via DataCite |
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IMAGES
COMMENTS
The new model of VPAs will be used to increase the interaction between humans and the machines by using different technologies, such as gesture recognition, image/video recognition, speech recognition, the vast dialogue and conversational knowledge base, and the general knowledge base.
PDF | On Jan 1, 2021, Mehdi Mekni published An Artificial Intelligence Based Virtual Assistant Using Conversational Agents | Find, read and cite all the research you need on ResearchGate.
The paper explores the potential of utilizing new technology to develop an intelligent Virtual Assistant that is capable of using natural language processing and user-based data.
In this research paper, we have studied and analyzed the working model and the efficiency of different virtual assistants available in the market. We also designed an intelligent virtual assistant that could be integrated with Google virtual services and work with the Google virtual assistant interface.
Artificial intelligence (AI) has lured consumers to orchestrate their routine activities relying on such technologies. Though AI-powered virtual assistants (AIVAs) have gained traction among service providers, these are still lagging on the demand front.
Leveraging recent advances in Large Language Models (LLMs), we introduce GptVoiceTasker, a virtual assistant poised to enhance user experiences and task efficiency on mobile devices. GptVoiceTasker excels at intelligently deciphering user commands and executing relevant device interactions to streamline task completion.