Talkback Smart Mirror Using Magic Mirror and Google Actions

Authors

  • I Khan Dept. of Computer Engineering, Bharati Vidyapeeth (Deemed to be University) College Of Engineering, Pune, India
  • A Jyotsna Dept. of Computer Engineering, Bharati Vidyapeeth (Deemed to be University) College Of Engineering, Pune, India
  • HV Singh Dept. of Computer Engineering, Bharati Vidyapeeth (Deemed to be University) College Of Engineering, Pune, India
  • S Rasal Dept. of Computer Engineering, Bharati Vidyapeeth (Deemed to be University) College Of Engineering, Pune, India

DOI:

https://doi.org/10.26438/ijcse/v8i5.168173

Keywords:

Google Actions Console, Google Assistant SDK, Google Cloud Console, Magic Mirror, Mic, Natural Language Processing, Raspberry pi, Scree, Speaker, Two way Mirror

Abstract

Smart voice assistants have gained a lot of popularity over the years and have been integrated with numerous devices. This paper aims to focus on the contribution of the voice assistant to ease our lifestyles. Amazon Echo, Google Home are some of the already existing smart assistants. Currently, these systems cannot visualize the results. The main aim of this project is to integrate these assistants with ambient displays, which in turn would lead to increased efficiency, accuracy, and ease of access. The talkback mirror can be used for information retrieval, for conversations, and entertainment of the user. It will cater to the queries of users, without them having to lift a finger.

References

[1] Bentley, F., Luvogt, C., Silverman, M., Wirasinghe, R., White, B. and Lottridge, D., 2018. Understanding the long-term use of smart speaker assistants. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2(3), pp.1-24.

[2] Wueest, C., 2017. Everything You Need to Know About the Security of Voice-Activated Smart Speakers. Symantec.(Nov. 2017).

[3] Norberg, F. and Yildirim, Z., 2018. The implementation of Voice Command in Smart Homes.

[4] Rieser, V. and Lemon, O., 2011. Reinforcement learning for adaptive dialogue systems: a data-driven methodology for dialogue management and natural language generation. Springer Science & Business Media.

[5] Newman, N., 2018. The future of voice and the implications for news.

Downloads

Published

2020-05-31
CITATION
DOI: 10.26438/ijcse/v8i5.168173
Published: 2020-05-31

How to Cite

[1]
I. Khan, A. Jyotsna, H. Singh, and S. Rasal, “Talkback Smart Mirror Using Magic Mirror and Google Actions”, Int. J. Comp. Sci. Eng., vol. 8, no. 5, pp. 168–173, May 2020.

Issue

Vol. 8 No. 5 (2020): IJCSE May Edition

Section

Survey Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.