76 citations · 284 across the 16 of their papers we have counts for
12 papers · 1 filter
Masked diffusion enables coherent beat tracking
Francesco Foscarin, Filip Korzeniowski, Richard Vogl
Current neural networks for beat tracking generate invalid outputs, such as consecutive downbeats and erratic tempo changes, even when these are not present in the training data. H…
Moisesdb: A dataset for source separation beyond 4-stems
Igor Pereira, Felipe Araújo, Filip Korzeniowski +1
In this paper, we introduce the MoisesDB dataset for musical source separation. It consists of 240 tracks from 45 artists, covering twelve musical genres. For each song, we provide…
Supervised and Unsupervised Learning of Audio Representations for Music Understanding
Matthew C. McCallum, Filip Korzeniowski, Sergio Oramas +2
In this work, we provide a broad comparative analysis of strategies for pre-training audio understanding models for several tasks in the music domain, including labelling of genre,…
Mood Classification Using Listening Data
Filip Korzeniowski, Oriol Nieto, Matthew McCallum +3
The mood of a song is a highly relevant feature for exploration and recommendation in large collections of music. These collections tend to require automatic methods for predicting…
Automatic Chord Recognition with Higher-Order Harmonic Language Modelling
Filip Korzeniowski, Gerhard Widmer
Common temporal models for automatic chord recognition model chord changes on a frame-wise basis. Due to this fact, they are unable to capture musical knowledge about chord progres…
Genre-Agnostic Key Classification With Convolutional Neural Networks
Filip Korzeniowski, Gerhard Widmer
We propose modifications to the model structure and training procedure to a recently introduced Convolutional Neural Network for musical key classification. These modifications ena…
Improved Chord Recognition by Combining Duration and Harmonic Language Models
Filip Korzeniowski, Gerhard Widmer
Chord recognition systems typically comprise an acoustic model that predicts chords for each audio frame, and a temporal model that casts these predictions into labelled chord segm…
Evaluating language models of tonal harmony
David R. W. Sears, Filip Korzeniowski, Gerhard Widmer
This study borrows and extends probabilistic language models from natural language processing to discover the syntactic properties of tonal harmony. Language models come in many sh…
On the Futility of Learning Complex Frame-Level Language Models for Chord Recognition
Filip Korzeniowski, Gerhard Widmer
Chord recognition systems use temporal models to post-process frame-wise chord preditions from acoustic models. Traditionally, first-order models such as Hidden Markov Models were…
On the Potential of Simple Framewise Approaches to Piano Transcription
Rainer Kelz, Matthias Dorfer, Filip Korzeniowski +3
In an attempt at exploring the limitations of simple approaches to the task of piano transcription (as usually defined in MIR), we conduct an in-depth analysis of neural network-ba…
Feature Learning for Chord Recognition: The Deep Chroma Extractor
Filip Korzeniowski, Gerhard Widmer
We explore frame-level audio feature learning for chord recognition using artificial neural networks. We present the argument that chroma vectors potentially hold enough informatio…
madmom: a new Python Audio and Music Signal Processing Library
Sebastian Böck, Filip Korzeniowski, Jan Schlüter +2
In this paper, we present madmom, an open-source audio processing and music information retrieval (MIR) library written in Python. madmom features a concise, NumPy-compatible, obje…