helpResearch questionMusic, Arts, and Performance Training
Can automated dance action recognition improve efficiency and experience in learners' annotation tasks?Education, Training, and Skill Development / Music, Arts, and Performance Training
Can automated dance action recognition improve efficiency and experience in learners' annotation tasks?
Similar questions
helpResearch questionMusic, Arts, and Performance Training
How can AI provide improvisational feedback and emotional support to improve learning experience and efficiency for self-taught guitar learners?helpResearch questionMusic, Arts, and Performance Training
Can combining audio analysis and gesture recognition effectively identify and correct technical errors in guitar learning?helpResearch questionMusic, Arts, and Performance Training
Can personalized learning paths and emotional support significantly improve music learners' practice persistence and motivation?helpResearch questionMusic, Arts, and Performance Training
How can low-cost multimodal data (e.g., video and keystroke data) be used to estimate small hand-muscle activity?helpResearch questionMusic, Arts, and Performance Training
How effective are estimation models combining video and keystroke data for small-muscle control training?helpResearch questionMusic, Arts, and Performance Training
Can an intuitive muscle-activity visualization interface help piano players optimize muscle use?Related papers
IUI 2025
FretMate: ChatGPT-Powered Adaptive Guitar Learning Assistant
Xin Shu, Lei Shi, Jiacheng Cheng
CHI 2025
PiaMuscle: Improving Piano Skill Acquisition by Cost-effectively Estimating and Visualizing Activities of Miniature Hand Muscles
Ruofan Liu, Yichen Peng, Takanori Oku
CHI 2025
CalliSence: An Interactive Educational Tool for Process-based learning in Chinese Calligraphy
Xinya Gong, Wenhui Tao, Yuxin Ma
CHI 2024
DoodleTunes: Interactive Visual Analysis of Music-Inspired Children Doodles with Automated Feature Annotation
Shuqi Liu, Jia Bu, Huayuan Ye
CHI 2024
Designing and Evaluating an Advanced Dance Video Comprehension Tool with In-situ Move Identification Capabilities
Saad Hassan, Caluã de Lacerda Pataca, Laleh Nourian
CHI 2023
Boards Hit Back: Reflecting on Martial Arts Practices Through Soma Design
Yoav Luft, Pavel Karpashevich, Kristina Höök
CHI 2022
Evaluating Singing for Computer Input Using Pitch, Interval, and Melody
Graeme Zinck, Daniel Vogel
CHI 2021
SonicHoop: Using Interactive Sonification to Support Aerial Hoop Practices
Wanyu Liu, Artem Dementyev, Diemo Schwarz
CHI 2021
Let’s Frets! Assisting Guitar Students during Practice via Capacitive Sensing
Karola Marky, Andreas Weiß, Andrii Matviienko