Die 50. Jahrestagung für Akustik – DAGA 2024 – findet vom 18. bis 21. März in Hannover statt. Das Fraunhofer IDMT stellt in zahlreichen Beiträgen aktuelle Forschungsergebnisse vor.
Unser Experte Jakob Abeßer organisiert gemeinsam mit Stefan Balke (Hochschule Weserbergland Hameln) und Meinard Müller (AudioLabs) die strukturierte Session »Sound Analysis für Music and Audio Signals«.
The development of computational methods for analyzing, segmenting, and classifying audio signals is of fundamental importance. As in general multimedia processing, many recent advances in audio processing (including speech, music, and environmental sounds) have been driven by deep learning (DL). In contrast to traditional audio engineering approaches, which directly exploit domain knowledge in the processing pipeline, DL-based approaches attempt to learn relevant patterns from (suitably annotated and structured) training data. In this session, we want to explore the benefits and limitations of model-based and data-driven techniques for learning task-specific sound event representations. Furthermore, we want to discuss explainable DL models that can better understand sound events' structural and acoustic properties. This session invites contributions that particularly address the following topics:
Fraunhofer-Institut für Digitale Medientechnologie IDMT