AI-Based Voice Assistance Using AWS
Keywords:
Conversational Agents, Human information Behaviour, Human Information Interactions, Intelligent Personal Assistants, Voice-Controlled AgentsAbstract
Amazon Alexa is a voice-controlled pplication that is rapidly gaining popularity. In this paper user interactions with this technology, and focused on the types of tasks requested of Alexa, the variables that affect user behaviours with Alexa, and Alexa's alternatives. AI
based voice assistance using AWS is offering the users a way to acquire such competence. Particularly, we focus on developing skills for the Alexa assistant, as it is the most widespread. It’s open a new world, a world where the user can talk to a machine as if it were a human and the machine will perform the work you request. Ideally, such conversations should be solely between the user and the voice assistance. For the hands-free feature that the user raved about and the other for speech recognition and understanding which is one key feature of the Echo.
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References
Lopatovska and H. Oropeza, “User interactions with ‘Alexa’ in public academic space,” Proc. Assoc. Inf. Sci. Technol., vol. 55, no. 1, pp. 309–318, Jan. 2018.
K. Pollmann, C. Ruff, K. Vetter, and G. Zimmermann, “Robot vs. voice assistant: Is playing with pepper more fun than playing with alexa?,” in ACM/IEEE International Conference on Human-Robot Interaction, 2020, pp. 395– 397.
Lopatovska, “Personality dimensions of intelligent personal assistants,” in CHIIR 2020 - Proceedings of the 2020 Conference on Human Information Interaction and Retrieval, 2020, pp. 333–337.
Kei Hashimoto, Junichi Yamagishi, William Byrne, Simon King, Keiichi Tokuda, “An analysis of machine translation and speech synthesis in speech-to-speech translation system” proceedings of 5108978-1-4577-0539- 7/11/$26.00 ©2011 IEEE.
How to build a Hello World Alexa Skill. https://tutorials.botsfloor.com/how-to-build-hello worldalexa-skill-bcea0d01ee8f
MIT App Inventor, https://appinventor.mit.edu/ [7] Hirschberg, Julia, and Christopher D.(2015). Manning. “Advances in Natural Language Processing.” Science 349 (6245): 261–266. doi:10.1126/science.aaa8685
K. Srihari, V. Sakthivel, G. V. K. Reddy, S. Subhasree, P. Sankavi, and E. Udayakumar, Implementation of Alexa Based Intelligent Voice Response System for Smart Campus, vol. 626. 2020.
H. Phatnani, Mr. J. Patra and Ankit Sharma’ “CHATBOT ASSISTING: SIRI” Proceedings of BITCON-2015 Innovations For National Development National Conference on Research and Development in Computer Science and Applications, E-ISSN2249–8974
Roussev, V. Barreto, A. and Ahmed, I. (2016). API-Based Forensic Acquisition of Cloud Drives. Advances in Digital Forensics XII, pp. 213-235.
1redDrop. Amazon Echo sold 11 Million deviced by Dec 1, 2016: Morgan Stanley. http://1reddrop.com/2017/01/23/amazonecho-sold-11- million-devices-by-december-1-says- morgan-stanley/ [Accessed Jan. 2017].
Gatner. Gartner Says Worldwide Spending on VPA Enabled Wireless Speakers Will Top
$2 Billion by 2020. https://www. gartner.com/newsroom/id/3464317 [Accessed Jan. 2017] [14] Deepak Shende, RiaUmahiya, Monika Raghorte, AishwaryaBhisikar, AnupBhange, “AI Based Voice Assistant Using Python”, Journal of Emerging Technologies and Innovative Research (JETIR), February 2019, Volume 6, Issue 2
M. A. Jawale, A. B. Pawar, D. N. Kyatanavar, “Smart Python Coding through Voice Recognition”, International
Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8 Issue 10, August 2019.
Hale, J. (2013). Amazon cloud drive forensic analysis. Digital Investigation, 10(3), pp. 259–265.
“Automatic question generation for decision tree based state tying,” Proc. of ICASSP, 1998
“Speech recognition with flat direct models,” IEEE Journal of Selected Topics in Signal Processing, 2010.
Kei Hashimoto, Junichi Yamagishi, William Byrne, Simon King, Keiichi Tokuda, “An analysis of machine translation and speech synthesis in speech-to-speech translation system” proceedings of 5108978-1-4577-0539- 7/11/$26.00 ©2011 IEEE.
