Uploaded November 2024 | Updated September 2026, 1 day ago
Cambridge PhD student Huijiang Wang from the Bio-Inspired #Robotics Laboratory (BIRL), Department of Engineering, and his co-authors present a collaborative robot that uses machine learning to predict the appropriate piano chord progressions based on a human’s piano playing. Experiments demonstrated a 93% accuracy rate.
Meanwhile, a behaviour-adaptive controller enables seamless temporal synchronisation to take place, so that the collaborative robot can generate harmonic chord accompaniment for the human-played melody in real time. In effect, both human and robot are playing a #duet.
Read the article: eng.cam.ac.uk/news/research-human-robot-cooperative-piano-playing-hits-high-note-ai-conference
View the open access research paper: doi.org/10.1109/TRO.2024.3484633
Reference:
Huijiang Wang; Xiaoping Zhang; Fumiya Iida. ‘Human-robot cooperative piano playing with learning-based real-time music accompaniment’. IEEE Transactions on Robotics (2024).
#MachineLearning
Cambridge PhD student Huijiang Wang from the Bio-Inspired #Robotics Laboratory (BIRL), Department of Engineering, and his co-authors present a collaborative robot that uses machine learning to predict the appropriate piano chord progressions based on a human’s piano playing. Experiments demonstrated a 93% accuracy rate.
Meanwhile, a behaviour-adaptive controller enables seamless temporal synchronisation to take place, so that the collaborative robot can generate harmonic chord accompaniment for the human-played melody in real time. In effect, both human and robot are playing a #duet.
Read the article: eng.cam.ac.uk/news/research-human-robot-cooperative-piano-playing-hits-high-note-ai-conference
View the open access research paper: doi.org/10.1109/TRO.2024.3484633
Reference:
Huijiang Wang; Xiaoping Zhang; Fumiya Iida. ‘Human-robot cooperative piano playing with learning-based real-time music accompaniment’. IEEE Transactions on Robotics (2024).
#MachineLearning
