Autrainer: A Modular and Extensible Deep Learning Toolkit for Computer Audition Tasks

MCML Authors

Andreas Triantafyllopoulos

→ Group Björn Schuller
 Health Informatics

Manuel Milling

→ Group Björn Schuller
 Health Informatics

Björn Schuller

Prof. Dr.

Principal Investigator

Health Informatics

Abstract

This work introduces the key operating principles for autrainer, our new deep learning training framework for computer audition tasks. autrainer is a PyTorch-based toolkit that allows for rapid, reproducible, and easily extensible training on a variety of different computer audition tasks. Concretely, autrainer offers low-code training and supports a wide range of neural networks as well as preprocessing routines. In this work, we present an overview of its inner workings and key capabilities.

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Preprint

Nov. 2024

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Authors

S. Rampp • A. Triantafyllopoulos • M. Milling • B. W. Schuller

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Links

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Research Area

 B3 | Multimodal Perception