2023 Program
Metaverse, Digital Media, Artificial Intelligence
2023.01.01-2023.12.31
This project mainly explores how to synthesize situational installation art with images and music through digital technology and artistic design. The method of learning images and generating music through artificial intelligence, from images to titles, titles to lyrics, and lyrics to music, forms music that combines images with a given style. This technology combines many professional fields, including the use of digital technology combined with animation games, interactive entertainment, and creative art design to achieve the planning and design of the metaverse.
2020 Program
Artificial intelligence, Machine Learning, Statistical Modeling
2020.01.01-2023.12.31
This project is focused on designing a virtual AI-based ChatBot. In order to achieve the accuracy of simulation AI characters, we must be familiar with the characteristics and personality of the characters. First, we will analyze the characteristics and the dialogue contexts of the characters by statistical analysis. Secondly, we will build the character model by machine learning. In order to allow the system to be more realistically applied to different characters, users can set the characteristics of the characters by themselves and the system can auto accomplish an AI model based on the needs of users.
In this project, students must have some basic programming skills and statistical background.
2019 Program
Artificial intelligence, Machine Learning, Music Signal Analysis
This project will build a system for Music Visualization on Robot that could automatically link the flashlight, color, and emotion through music. We call this system an MVR algorithm composed of two analyses: music signal analysis and music sentiment analysis. People who want to join this project should have basic programming skills such as Python, JavaScript, C#, etc. We will first implement the MVR algorithm on a robot called Zenbo, released by ASUS Company. For extensive applications, the MVR system would be carried out not only in Zenbo robot but also extended to other fields of Artificial Intelligent (AI) equipment in the future.
2018 Program
Database, Algorithm, Recommender System
An algorithm design for a Recommender System based on a Kansei model will be discussed in this project, we called this algorithm as Kansei Recommender System (KRS). The purpose of the KRS algorithm is designed to support designers to pre-know the appearance feeling (Kansei) of products from consumers. To complete this algorithm, you need to design the algorithm system through three small projects: (1) Extract Kansei factors and evaluation factors from consumers’ shopping items. (2) Determine a Kansei model for the KRS algorithm. (3) Making decisions by using the KRS algorithm. In the end, you need to have a case study for real data analysis.
Database, Algorithm, Recommender System.