Search Results for author: Florian Henkel

Found 11 papers, 6 papers with code

Similar but Faster: Manipulation of Tempo in Music Audio Embeddings for Tempo Prediction and Search

no code implementations17 Jan 2024 Matthew C. McCallum, Florian Henkel, Jaehun Kim, Samuel E. Sandberg, Matthew E. P. Davies

We propose tempo translation functions that allow for efficient manipulation of tempo within a pre-existing embedding space whilst maintaining other properties such as genre.

Data Augmentation Retrieval +1

On the Effect of Data-Augmentation on Local Embedding Properties in the Contrastive Learning of Music Audio Representations

no code implementations17 Jan 2024 Matthew C. McCallum, Matthew E. P. Davies, Florian Henkel, Jaehun Kim, Samuel E. Sandberg

Similarly, we show that the optimal selection of data augmentation strategies for contrastive learning of music audio embeddings is dependent on the downstream task, highlighting this as an important embedding design decision.

Contrastive Learning Data Augmentation

Fully Automatic Page Turning on Real Scores

1 code implementation12 Nov 2021 Florian Henkel, Stephanie Schwaiger, Gerhard Widmer

We present a prototype of an automatic page turning system that works directly on real scores, i. e., sheet images, without any symbolic representation.

Position

Over-Parameterization and Generalization in Audio Classification

no code implementations19 Jul 2021 Khaled Koutini, Hamid Eghbal-zadeh, Florian Henkel, Jan Schlüter, Gerhard Widmer

Convolutional Neural Networks (CNNs) have been dominating classification tasks in various domains, such as machine vision, machine listening, and natural language processing.

Acoustic Scene Classification Audio Classification +1

Multi-modal Conditional Bounding Box Regression for Music Score Following

1 code implementation10 May 2021 Florian Henkel, Gerhard Widmer

This paper addresses the problem of sheet-image-based on-line audio-to-score alignment also known as score following.

Data Augmentation object-detection +2

Learning to Read and Follow Music in Complete Score Sheet Images

1 code implementation21 Jul 2020 Florian Henkel, Rainer Kelz, Gerhard Widmer

This paper addresses the task of score following in sheet music given as unprocessed images.

Position

Audio-Conditioned U-Net for Position Estimation in Full Sheet Images

1 code implementation16 Oct 2019 Florian Henkel, Rainer Kelz, Gerhard Widmer

The goal of score following is to track a musical performance, usually in the form of audio, in a corresponding score representation.

Multimodal Deep Learning Position

Learning to Listen, Read, and Follow: Score Following as a Reinforcement Learning Game

1 code implementation17 Jul 2018 Matthias Dorfer, Florian Henkel, Gerhard Widmer

Score following is the process of tracking a musical performance (audio) with respect to a known symbolic representation (a score).

Decision Making reinforcement-learning +1

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