Conversational agent in HCI a review

Research Article
Open access

Conversational agent in HCI a review

Yixuan Zhao 1* , Tianbo Lin 2 , Yize Wang 3
  • 1 Guangdong Normal University of Technology    
  • 2 Stamford American International school of Singapore    
  • 3 EIC Education: MINDMAX    
  • *corresponding author zhaoyixuan_137@qq.com
Published on 26 February 2024 | https://doi.org/10.54254/2755-2721/43/20230807
ACE Vol.43
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-83558-311-1
ISBN (Online): 978-1-83558-312-8

Abstract

Nowadays, AI technology is developing rapidly and slowly covering all areas of life. AI facilitates different parts of our lives and provides us with a lot of help. For example, in learning, students can acquire knowledge more conveniently through AI, and buyers can find suitable goods more conveniently through AI when shopping. At the same time, more and more technology is used in the field of voice agents, which allows humans to enjoy a lot of better services. In this article, we will study to better understand "how to understand human natural language and how the repository of knowledge is built." In the article we build with examples and deep learning models (CNN and RNN) through databases. Through repeated research and analysis, we can find that there are some limitations in this paper, such as the single learning model and the insufficient elaboration of data analysis and signal system technology. But at the same time, we also found a lot of future application prospects that voice agents can develop, it can be applied in many fields, such as finance, medical care, education and so on. For example, in children's education, parents can use voice agents to set time limits and monitor their children's progress. Existing digital interactive storytelling systems have limitations in terms of available storybooks and hand-crafted issues. Voice agents are becoming more popular in everyday scenarios, and more users are adopting devices like Siri and Google Assistant. In the future, conversational agents are expected to play an important role in oral communication with users.

Keywords:

Conversational agent, CNN, RNN, Artificial intelligence

Zhao,Y.;Lin,T.;Wang,Y. (2024). Conversational agent in HCI a review. Applied and Computational Engineering,43,49-58.
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References

[1]. Young, R. M., & Moore, J. D. (2018). Conversational AI: The science behind the Alexa Prize. AI Magazine, 39(3), 25-34.

[2]. Schlangen, D. (2017). Situated interaction with embodied conversational agents. Synthesis Lectures on Human Language Technologies, 10(2), 1-184.

[3]. Porcheron, M., Fischer, J. E., & Sharples, S. (2018). Voice interfaces in everyday life. Human–Computer Interaction, 1-36.

[4]. Ali, A. (n.d.). Conversational AI chatbot based on encoder-decoder architectures with ... https://www.researchgate.net/publication/338100972_Conversational_AI_Chatbot_Based_on_Encoder-Decoder_Architectures_with_Attention_Mechanism

[5]. Ali, N. (n.d.). Chatbot: A Conversational Agent employed with Named Entity Recognition Model using Artificial Neural Network

[6]. Jackylyn L. Beredo, Ethel C. Ong. (n.d.). A Hybrid Response Generation Model for an Empathetic Conversational Agent.

[7]. Kenro Go, Toshiki Onishi, Asahi Ogushi, Akihiro Miyata. (n.d.). Conversational Agents Replying with a Manzai-style Joke

[8]. Chunjong Par, Chulhong Min, Sourav Bhattacharya, Fahim Kawsar. (n.d.). Augmenting Conversational Agents with Ambient Acoustic Contexts

[9]. Kenro Go (2021) Conversational Agents Replying with a Manzai-style Joke. 221-230

[10]. Zheng Zhang (2021) Building a storytelling conversational agent through parent-AI collaboration.1-6

Cite this article

Zhao,Y.;Lin,T.;Wang,Y. (2024). Conversational agent in HCI a review. Applied and Computational Engineering,43,49-58.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Machine Learning and Automation

ISBN：978-1-83558-311-1(Print) / 978-1-83558-312-8(Online)
Editor：Mustafa İSTANBULLU
Conference website: https://2023.confmla.org/
Conference date: 18 October 2023
Series: Applied and Computational Engineering
Volume number: Vol.43
ISSN：2755-2721(Print) / 2755-273X(Online)

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References

[1]. Young, R. M., & Moore, J. D. (2018). Conversational AI: The science behind the Alexa Prize. AI Magazine, 39(3), 25-34.

[2]. Schlangen, D. (2017). Situated interaction with embodied conversational agents. Synthesis Lectures on Human Language Technologies, 10(2), 1-184.

[3]. Porcheron, M., Fischer, J. E., & Sharples, S. (2018). Voice interfaces in everyday life. Human–Computer Interaction, 1-36.

[4]. Ali, A. (n.d.). Conversational AI chatbot based on encoder-decoder architectures with ... https://www.researchgate.net/publication/338100972_Conversational_AI_Chatbot_Based_on_Encoder-Decoder_Architectures_with_Attention_Mechanism

[5]. Ali, N. (n.d.). Chatbot: A Conversational Agent employed with Named Entity Recognition Model using Artificial Neural Network

[6]. Jackylyn L. Beredo, Ethel C. Ong. (n.d.). A Hybrid Response Generation Model for an Empathetic Conversational Agent.

[7]. Kenro Go, Toshiki Onishi, Asahi Ogushi, Akihiro Miyata. (n.d.). Conversational Agents Replying with a Manzai-style Joke

[8]. Chunjong Par, Chulhong Min, Sourav Bhattacharya, Fahim Kawsar. (n.d.). Augmenting Conversational Agents with Ambient Acoustic Contexts

[9]. Kenro Go (2021) Conversational Agents Replying with a Manzai-style Joke. 221-230

[10]. Zheng Zhang (2021) Building a storytelling conversational agent through parent-AI collaboration.1-6

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