Multi-modal Conditional Bounding Box Regression for Music Score Following

• URL: http://arxiv.org/abs/2105.04309v1
• Date: Mon, 10 May 2021 12:43:35 GMT
• Title: Multi-modal Conditional Bounding Box Regression for Music Score Following
• Authors: Florian Henkel and Gerhard Widmer
• Abstract summary: This paper addresses the problem of sheet-image-based on-line audio-to-score alignment also known as score following. A conditional neural network architecture is proposed that directly predicts x,y coordinates of the matching positions in a complete score sheet image at each point in time for a given musical performance.
• Score: 7.360807642941713
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper addresses the problem of sheet-image-based on-line audio-to-score alignment also known as score following. Drawing inspiration from object detection, a conditional neural network architecture is proposed that directly predicts x,y coordinates of the matching positions in a complete score sheet image at each point in time for a given musical performance. Experiments are conducted on a synthetic polyphonic piano benchmark dataset and the new method is compared to several existing approaches from the literature for sheet-image-based score following as well as an Optical Music Recognition baseline. The proposed approach achieves new state-of-the-art results and furthermore significantly improves the alignment performance on a set of real-world piano recordings by applying Impulse Responses as a data augmentation technique.

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