The Holistic Evaluation of Audio Representations (HEAR) (https://neuralaudio.ai/
) welcomes submissions to our PMLR special issue.
What audio embedding approach generalizes best to a wide range of downstream tasks across a variety of everyday domains without fine-tuning?
The aim of the HEAR benchmark is to develop a general-purpose audio representation that provides a strong basis for learning in a wide variety of tasks and scenarios. HEAR evaluates audio representations using a benchmark suite across a variety of domains, including speech, environmental sound, and music.
Call for Papers
We welcome research addressing the topic of general-purpose audio representations and the holistic evaluation of audio representations. Submissions are strongly encouraged to present results on the 19 HEAR benchmark tasks (https://neuralaudio.ai/hear-tasks.html
) and possibly use the models submitted to the HEAR 2021 NeurIPS challenge. Submissions from all authors are welcome, even if you did not participate in the NeurIPS challenge.
Submissions are open on OpenReview. There is no page limit.
Submission deadline: June 30th, 2022 AoE.
For more information and to submit please see:
Joseph Turian and Björn W. Schuller and Dorien Herremans and Katrin Kirchhoff and Paola Garcia Perera and Philippe Esling.