Voice and image recognition for smart pet app

Nowadays, there are many people feel depressed and lonely. The propose of this project is to develop a Smart Pet Application which is an Android application that can interact with people to reduce their loneliness. There are two parts in the Smart Pet Application: 1. Game design and logics. 2. Artif...

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Main Author: Lee, Yen Long
Format: Final Year Project / Dissertation / Thesis
Published: 2019
Subjects:
Online Access:http://eprints.utar.edu.my/3496/
http://eprints.utar.edu.my/3496/1/CS%2D2019%2D1603235%2D1.pdf
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author Lee, Yen Long
author_facet Lee, Yen Long
author_sort Lee, Yen Long
building UTAR Institutional Repository
collection Online Access
description Nowadays, there are many people feel depressed and lonely. The propose of this project is to develop a Smart Pet Application which is an Android application that can interact with people to reduce their loneliness. There are two parts in the Smart Pet Application: 1. Game design and logics. 2. Artificial intelligence (AI) engine to perform voice and image recognition. This report will focus on second part, which is descript how the AI engine work. In the propose system, TensorFlow Sequence-to-Sequence (tf-seq2seq) Model is used to be the machine learning model to let the Smart Pet can communicate with its owner. tf-seq2seq is a general-purpose encoder-decoder framework for TensorFlow that suitable for Conversational Modelling. On the other hand, Baidu Cloud face recognition SDK is used for the system to let the Smart Pet perform face recognition in order to recognize its owner. Baidu Cloud face recognition is a component on Baidu Cloud Computing Platform that suitable for real-time object recognition. We will combine the game design and logics together with the AI engine to become a complete Smart Pet Application.
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format Final Year Project / Dissertation / Thesis
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institution Universiti Tunku Abdul Rahman
institution_category Local University
last_indexed 2025-11-15T19:30:12Z
publishDate 2019
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spelling utar-34962019-08-20T04:12:48Z Voice and image recognition for smart pet app Lee, Yen Long Q Science (General) Nowadays, there are many people feel depressed and lonely. The propose of this project is to develop a Smart Pet Application which is an Android application that can interact with people to reduce their loneliness. There are two parts in the Smart Pet Application: 1. Game design and logics. 2. Artificial intelligence (AI) engine to perform voice and image recognition. This report will focus on second part, which is descript how the AI engine work. In the propose system, TensorFlow Sequence-to-Sequence (tf-seq2seq) Model is used to be the machine learning model to let the Smart Pet can communicate with its owner. tf-seq2seq is a general-purpose encoder-decoder framework for TensorFlow that suitable for Conversational Modelling. On the other hand, Baidu Cloud face recognition SDK is used for the system to let the Smart Pet perform face recognition in order to recognize its owner. Baidu Cloud face recognition is a component on Baidu Cloud Computing Platform that suitable for real-time object recognition. We will combine the game design and logics together with the AI engine to become a complete Smart Pet Application. 2019-04-22 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/3496/1/CS%2D2019%2D1603235%2D1.pdf Lee, Yen Long (2019) Voice and image recognition for smart pet app. Final Year Project, UTAR. http://eprints.utar.edu.my/3496/
spellingShingle Q Science (General)
Lee, Yen Long
Voice and image recognition for smart pet app
title Voice and image recognition for smart pet app
title_full Voice and image recognition for smart pet app
title_fullStr Voice and image recognition for smart pet app
title_full_unstemmed Voice and image recognition for smart pet app
title_short Voice and image recognition for smart pet app
title_sort voice and image recognition for smart pet app
topic Q Science (General)
url http://eprints.utar.edu.my/3496/
http://eprints.utar.edu.my/3496/1/CS%2D2019%2D1603235%2D1.pdf