6 citations · 19 across the 24 of their papers we have counts for
23 papers · 1 filter
Restore, Separate, Restore: A Modular Framework for Music Source Restoration
Tobias Morocutti, Emmanouil Karystinaios, Gerhard Widmer
Music Source Restoration (MSR) seeks to recover original, unprocessed instrument stems from mixed, mastered, and possibly degraded recordings. Unlike conventional source separation…
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,…
Neural Morphing: Sequence-Optimized Token-Level Morphing in Neural Audio Codecs
Emmanouil Karystinaios
Neural audio codecs were originally developed for high-fidelity compression; however, their latent token representations and expressive decoders also constitute a powerful substrat…
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…
Low-Latency Neural Models for Real-Time Music Enhancement
Emmanouil Karystinaios, Jonathan Greif, David Nadrchal +2
Music recordings and live streams are often affected by noise, reverberation, spectral imbalances, or artifacts that degrade listening quality. While speech enhancement has matured…
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…
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…
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…
WeaveMuse: An Open Agentic System for Multimodal Music Understanding and Generation
Emmanouil Karystinaios
Agentic AI has been standardized in industry as a practical paradigm for coordinating specialized models and tools to solve complex multimodal tasks. In this work, we present Weave…
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…
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…
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…
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…
Sounding Out Reconstruction Error-Based Evaluation of Generative Models of Expressive Performance
Silvan David Peter, Carlos Eduardo Cancino-Chacón, Emmanouil Karystinaios +1
Generative models of expressive piano performance are usually assessed by comparing their predictions to a reference human performance. A generative algorithm is taken to be better…
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…
Roman Numeral Analysis with Graph Neural Networks: Onset-wise Predictions from Note-wise Features
Emmanouil Karystinaios, Gerhard Widmer
Roman Numeral analysis is the important task of identifying chords and their functional context in pieces of tonal music. This paper presents a new approach to automatic Roman Nume…
The ACCompanion: Combining Reactivity, Robustness, and Musical Expressivity in an Automatic Piano Accompanist
Carlos Cancino-Chacón, Silvan Peter, Patricia Hu +5
This paper introduces the ACCompanion, an expressive accompaniment system. Similarly to a musician who accompanies a soloist playing a given musical piece, our system can produce a…
Musical Voice Separation as Link Prediction: Modeling a Musical Perception Task as a Multi-Trajectory Tracking Problem
Emmanouil Karystinaios, Francesco Foscarin, Gerhard Widmer
This paper targets the perceptual task of separating the different interacting voices, i.e., monophonic melodic streams, in a polyphonic musical piece. We target symbolic music, wh…
Cadence Detection in Symbolic Classical Music using Graph Neural Networks
Emmanouil Karystinaios, Gerhard Widmer
Cadences are complex structures that have been driving music from the beginning of contrapuntal polyphony until today. Detecting such structures is vital for numerous MIR tasks suc…
The match file format: Encoding Alignments between Scores and Performances
Francesco Foscarin, Emmanouil Karystinaios, Silvan David Peter +3
This paper presents the specifications of match: a file format that extends a MIDI human performance with note-, beat-, and downbeat-level alignments to a corresponding musical sco…
Partitura: A Python Package for Symbolic Music Processing
Carlos Cancino-Chacón, Silvan David Peter, Emmanouil Karystinaios +3
Partitura is a lightweight Python package for handling symbolic musical information. It provides easy access to features commonly used in music information retrieval tasks, like no…