Andreas Arzt

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The Austrian Research Institute for Artificial Intelligence ∙ Johannes Kepler University Linz

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Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification

Distribution mismatches between the data seen at training and at applica...
09/04/2019 ∙ by Paul Primus, et al. ∙ 0 ∙ share

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Learning Complex Basis Functions for Invariant Representations of Audio

Learning features from data has shown to be more successful than using h...
07/13/2019 ∙ by Stefan Lattner, et al. ∙ 2 ∙ share

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Learning Soft-Attention Models for Tempo-invariant Audio-Sheet Music Retrieval

Connecting large libraries of digitized audio recordings to their corres...
06/26/2019 ∙ by Stefan Balke, et al. ∙ 0 ∙ share

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Cross-Modal Music Retrieval and Applications: An Overview of Key Methodologies

There has been a rapid growth of digitally available music data, includi...
02/12/2019 ∙ by Meinard Müller, et al. ∙ 0 ∙ share

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Audio-to-Score Alignment using Transposition-invariant Features

Audio-to-score alignment is an important pre-processing step for in-dept...
07/19/2018 ∙ by Andreas Arzt, et al. ∙ 0 ∙ share

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The ACCompanion v0.1: An Expressive Accompaniment System

In this paper we present a preliminary version of the ACCompanion, an ex...
11/07/2017 ∙ by Carlos Cancino-Chacón, et al. ∙ 0 ∙ share

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Aktuelle Entwicklungen in der Automatischen Musikverfolgung

In this paper we present current trends in real-time music tracking (a.k...
08/07/2017 ∙ by Andreas Arzt, et al. ∙ 0 ∙ share

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Learning Audio - Sheet Music Correspondences for Score Identification and Offline Alignment

This work addresses the problem of matching short excerpts of audio with...
07/31/2017 ∙ by Matthias Dorfer, et al. ∙ 0 ∙ share

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Modeling Harmony with Skip-Grams

String-based (or viewpoint) models of tonal harmony often struggle with ...
07/14/2017 ∙ by David R. W. Sears, et al. ∙ 0 ∙ share

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Towards Score Following in Sheet Music Images

This paper addresses the matching of short music audio snippets to the c...
12/15/2016 ∙ by Matthias Dorfer, et al. ∙ 0 ∙ share

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