1 citations · 1 across the 4 of their papers we have counts for
9 papers
A Flexible Encoding Model for Non-Unique Note Alignments
Suhit Chiruthapudi, Adam Å tefunko, Silvan Peter +3
Symbolic music alignment links notes in a symbolic performance to their counterparts in a score. While existing alignment encoding formats provide unique correspondences between th…
Score-Agnostic Structure Analysis in Large-Scale Performance Datasets
Patricia Hu, Silvan Peter, Gerhard Widmer
In recent years, thanks to advances in automatic music transcription (AMT), several large-scale datasets of automatically transcribed piano solo music have been released. While the…
Precise and Simple Audio-to-Score Alignment
Silvan Peter, Patricia Hu, Gerhard Widmer
Audio-to-score alignment is a long-standing challenge in music information retrieval and arguably the most widely applicable alignment task for music research. Alignment algorithms…
Sound and Music Biases in Deep Music Transcription Models: A Systematic Analysis
Lukáš Samuel Marták, Patricia Hu, Gerhard Widmer
Automatic Music Transcription (AMT) -- the task of converting music audio into note representations -- has seen rapid progress, driven largely by deep learning systems. Due to the…
Exploring System Adaptations For Minimum Latency Real-Time Piano Transcription
Patricia Hu, Silvan David Peter, Jan Schlüter +1
Advances in neural network design and the availability of large-scale labeled datasets have driven major improvements in piano transcription. Existing approaches target either offl…
Pairing Real-Time Piano Transcription with Symbol-level Tracking for Precise and Robust Score Following
Silvan Peter, Patricia Hu, Gerhard Widmer
Real-time music tracking systems follow a musical performance and at any time report the current position in a corresponding score. Most existing methods approach this problem excl…