6 papers
On a Separate Note: Robust Score-Informed Note Separation with a Two-Stream TFC-TDF U-Net and Adaptive Set Ownership
Benjamin Shiue-Hal Chou, Purvish Jajal, Nicholas John Eliopoulos +5
Score-informed note separation seeks to extract the performed waveform of all individual notes, often from a polyphonic recording. Existing deep learning systems generally only tar…
Real-Time Cellist Postural Evaluation With On-Device Computer Vision
Paolo Wang, Michael Zhang, Shrinand Perumal +14
Posture is a critical factor for beginning instrumental learners. Most students receive instruction only once a week, and during the intervals between lessons they have little or n…
Advancing Multi-Instrument Music Transcription: Results from the 2025 AMT Challenge
Ojas Chaturvedi, Kayshav Bhardwaj, Tanay Gondil +5
This paper presents the results of the 2025 Automatic Music Transcription (AMT) Challenge, an online competition to benchmark progress in multi-instrument transcription. Eight team…
From Score to Sound: An End-to-End MIDI-to-Motion Pipeline for Robotic Cello Performance
Samantha Sudhoff, Pranesh Velmurugan, Jiashu Liu +3
Robot musicians require precise control to obtain proper note accuracy, sound quality, and musical expression. Performance of string instruments, such as violin and cello, presents…
LadderSym: A Multimodal Interleaved Transformer for Music Practice Error Detection
Benjamin Shiue-Hal Chou, Purvish Jajal, Nick John Eliopoulos +4
Music learners can greatly benefit from tools that accurately detect errors in their practice. Existing approaches typically compare audio recordings to music scores using heuristi…
Detecting Music Performance Errors with Transformers
Benjamin Shiue-Hal Chou, Purvish Jajal, Nicholas John Eliopoulos +6
Beginner musicians often struggle to identify specific errors in their performances, such as playing incorrect notes or rhythms. There are two limitations in existing tools for mus…