1 citations · 5 across the 22 of their papers we have counts for
23 papers
ScorePrompts: Natural-Language Exploration of Symbolic Music Scores through Analysis
Emmanouil Karystinaios, Gerhard Widmer
We present ScorePrompts, an interactive system in which users upload a score, receive natural-language descriptions of its musical structure, ask questions about specific passages,…
From Prediction to Collaboration: Interactive Symbolic Music Analysis
Emmanouil Karystinaios, Johannes Hentschel, Markus Neuwirth +1
Automatic symbolic music analysis has made substantial progress, yet existing systems are typically designed for a single mode of use, such as full-score prediction, and therefore…
Dilemmadata: On the Interoperability of Heterogeneous Roman Numeral Datasets
Johannes Hentschel, Emmanouil Karystinaios, Gerhard Widmer +1
In recent years, there has been growing effort to annotate and collect large-scale corpora of Roman numeral analyses in support of data-driven studies in tonal harmony. We introduc…
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…
Multi-Stage Music Source Restoration with BandSplit-RoFormer Separation and HiFi++ GAN
Tobias Morocutti, Emmanouil Karystinaios, Jonathan Greif +1
Music Source Restoration (MSR) targets recovery of original, unprocessed instrument stems from fully mixed and mastered audio, where production effects and distribution artifacts v…
How Far Can Pretrained LLMs Go in Symbolic Music? Controlled Comparisons of Supervised and Preference-based Adaptation
Deepak Kumar, Emmanouil Karystinaios, Gerhard Widmer +1
Music often shares notable parallels with language, motivating the use of pretrained large language models (LLMs) for symbolic music understanding and generation. Despite growing i…
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…
MUSE-Explainer: Counterfactual Explanations for Symbolic Music Graph Classification Models
Baptiste Hilaire, Emmanouil Karystinaios, Gerhard Widmer
Interpretability is essential for deploying deep learning models in symbolic music analysis, yet most research emphasizes model performance over explanation. To address this, we in…
EngravingGNN: A Hybrid Graph Neural Network for End-to-End Piano Score Engraving
Emmanouil Karystinaios, Francesco Foscarin, Gerhard Widmer
This paper focuses on automatic music engraving, i.e., the creation of a humanly-readable musical score from musical content. This step is fundamental for all applications that inc…
AnalysisGNN: Unified Music Analysis with Graph Neural Networks
Emmanouil Karystinaios, Johannes Hentschel, Markus Neuwirth +1
Recent years have seen a boom in computational approaches to music analysis, yet each one is typically tailored to a specific analytical domain. In this work, we introduce Analysis…
Optical Music Recognition of Jazz Lead Sheets
Juan Carlos Martinez-Sevilla, Francesco Foscarin, Patricia Garcia-Iasci +3
In this paper, we address the challenge of Optical Music Recognition (OMR) for handwritten jazz lead sheets, a widely used musical score type that encodes melody and chords. The ta…
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…
How to Infer Repeat Structures in MIDI Performances
Silvan Peter, Patricia Hu, Gerhard Widmer
MIDI performances are generally expedient in performance research and music information retrieval, and even more so if they can be connected to a score. This connection is usually…
Language Models for Music Medicine Generation
Emmanouil Nikolakakis, Joann Ching, Emmanouil Karystinaios +3
Music therapy has been shown in recent years to provide multiple health benefits related to emotional wellness. In turn, maintaining a healthy emotional state has proven to be effe…
Quantifying the Corpus Bias Problem in Automatic Music Transcription Systems
Lukáš Samuel Marták, Patricia Hu, Gerhard Widmer
Automatic Music Transcription (AMT) is the task of recognizing notes in audio recordings of music. The State-of-the-Art (SotA) benchmarks have been dominated by deep learning syste…
Beat this! Accurate beat tracking without DBN postprocessing
Francesco Foscarin, Jan Schlüter, Gerhard Widmer
We propose a system for tracking beats and downbeats with two objectives: generality across a diverse music range, and high accuracy. We achieve generality by training on multiple…
GraphMuse: A Library for Symbolic Music Graph Processing
Emmanouil Karystinaios, Gerhard Widmer
Graph Neural Networks (GNNs) have recently gained traction in symbolic music tasks, yet a lack of a unified framework impedes progress. Addressing this gap, we present GraphMuse, a…
Cluster and Separate: a GNN Approach to Voice and Staff Prediction for Score Engraving
Francesco Foscarin, Emmanouil Karystinaios, Eita Nakamura +1
This paper approaches the problem of separating the notes from a quantized symbolic music piece (e.g., a MIDI file) into multiple voices and staves. This is a fundamental part of t…
Towards Musically Informed Evaluation of Piano Transcription Models
Patricia Hu, Lukáš Samuel Marták, Carlos Cancino-Chacón +1
Automatic piano transcription models are typically evaluated using simple frame- or note-wise information retrieval (IR) metrics. Such benchmark metrics do not provide insights int…
SMUG-Explain: A Framework for Symbolic Music Graph Explanations
Emmanouil Karystinaios, Francesco Foscarin, Gerhard Widmer
In this work, we present Score MUsic Graph (SMUG)-Explain, a framework for generating and visualizing explanations of graph neural networks applied to arbitrary prediction tasks on…
Perception-Inspired Graph Convolution for Music Understanding Tasks
Emmanouil Karystinaios, Francesco Foscarin, Gerhard Widmer
We propose a new graph convolutional block, called MusGConv, specifically designed for the efficient processing of musical score data and motivated by general perceptual principles…
8+8=4: Formalizing Time Units to Handle Symbolic Music Durations
Emmanouil Karystinaios, Francesco Foscarin, Florent Jacquemard +3
This paper focuses on the nominal durations of musical events (notes and rests) in a symbolic musical score, and on how to conveniently handle these in computer applications. We pr…
The Batik-plays-Mozart Corpus: Linking Performance to Score to Musicological Annotations
Patricia Hu, Gerhard Widmer
We present the Batik-plays-Mozart Corpus, a piano performance dataset combining professional Mozart piano sonata performances with expert-labelled scores at a note-precise level. T…