collaborators

7 papers

cs.SD2026

Transformer-Based Rhythm Quantization of Performance MIDI Using Beat Annotations

Maximilian Wachter, Sebastian Murgul, Michael Heizmann

Rhythm transcription is a key subtask of notation-level Automatic Music Transcription (AMT). While deep learning models have been extensively used for detecting the metrical grid i…

cs.SD2025

Beat-Based Rhythm Quantization of MIDI Performances

Maximilian Wachter, Sebastian Murgul, Michael Heizmann

We propose a transformer-based rhythm quantization model that incorporates beat and downbeat information to quantize MIDI performances into metrically-aligned, human-readable score…

cs.SD2025

Exploring Procedural Data Generation for Automatic Acoustic Guitar Fingerpicking Transcription

Sebastian Murgul, Michael Heizmann

Automatic transcription of acoustic guitar fingerpicking performances remains a challenging task due to the scarcity of labeled training data and legal constraints connected with m…

cs.SD2025

Joint Transcription of Acoustic Guitar Strumming Directions and Chords

Sebastian Murgul, Johannes Schimper, Michael Heizmann

Automatic transcription of guitar strumming is an underrepresented and challenging task in Music Information Retrieval (MIR), particularly for extracting both strumming directions…

cs.SD2025

Beat and Downbeat Tracking in Performance MIDI Using an End-to-End Transformer Architecture

Sebastian Murgul, Michael Heizmann

Beat tracking in musical performance MIDI is a challenging and important task for notation-level music transcription and rhythmical analysis, yet existing methods primarily focus o…

cs.SD2025

Fine-Tuning MIDI-to-Audio Alignment using a Neural Network on Piano Roll and CQT Representations

Sebastian Murgul, Moritz Reiser, Michael Heizmann +1

In this paper, we present a neural network approach for synchronizing audio recordings of human piano performances with their corresponding loosely aligned MIDI files. The task is…