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Listener Acoustic Personalisation (LAP) Challenge

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A benchmarking campaign on acoustic and non-acoustic factors in immersive technologies.

Personalized Head-Related Transfer Functions (HRTFs) have shown promise in enhancing auditory localization and immersion in mixed realities. However, relevant issues such as the accurate acquisition of user-specific anatomical data, efficient simulation algorithms, and effective user validation do not converge into a common and internationally recognized benchmark for evaluating HRTFs.

The LAP Challenge endeavours to provide a platform where researchers can explore these challenges, advance the state of the art, and contribute to the development of standardized metrics for personalised spatial audio.

The inaugural edition of the challenge will concentrate on two fundamental aspects of HRTF: spatial sampling and interpolation. Teams are challenged to submit their solutions that address one of two tasks:

  • Task 1: HRTF normalisation for merging different HRTF datasets
  • Task 2: spatial upsampling for obtaining a high-spatial-resolution HRTF from a very low number of directions

Results and Publications

There are two main publications related to the 1st Listener Acoustic Personalisation (LAP) Challenge:

These two publications open the LAP24 Special Topic in the IEEE Open Journal of Signal Processing, which will collect scientific contributions from participants in the LAP Challenge 2024

A draft technical report covering the full results of the challenge is also available here:

Published Approaches for Task 2: HRTF Upsampling

The following papers describe approaches submitted to or evaluated in Task 2 of the LAP Challenge:

1. Hogg, A. O. T., Jenkins, M., Liu, H., Squires, I., Cooper, S. J., & Picinali, L. (2024). HRTF Upsampling With a Generative Adversarial Network Using a Gnomonic Equiangular Projection. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 32, 2085–2099.

2. Zhao, J., Yao, D., & Li, J. (2025). Head-Related Transfer Function Upsampling With Spatial Extrapolation Features. IEEE Transactions on Audio, Speech and Language Processing, 33, 1034–1048.

3. Arevalo, C., & Villegas, J. (2025). Spatial Upsampling of Head-Related Impulse Responses via Elevation-Wise Encoder-Decoder Networks. IEEE Open Journal of Signal Processing, 6, 1086–1093.

4. Masuyama, Y., Wichern, G., Germain, F. G., Ick, C., & Le Roux, J. (2026). RANF: Neural Field-Based HRTF Spatial Upsampling With Retrieval Augmentation and Parameter Efficient Fine-Tuning. IEEE Open Journal of Signal Processing, 7, 32–41.

5. Arend, J. M., Pörschmann, C., Weinzierl, S., & Brinkmann, F. (2023). Magnitude-Corrected and Time-Aligned Interpolation of Head-Related Transfer Functions. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 31, 3783–3799.

6. Ito, Y., Nakamura, T., Koyama, S., & Saruwatari, H. (2022). Head-Related Transfer Function Interpolation From Spatially Sparse Measurements Using Autoencoder With Source Position Conditioning. International Workshop on Acoustic Signal Enhancement (IWAENC), 1–5.

Task 2: HRTF Upsampling – Perceptual Evaluation and HRTF Dataset

A perceptual study was conducted to evaluate the HRTFs produced by the Task 2 upsampling approaches. The complete collection of HRTFs used in the evaluation, together with the study materials and results, has been made publicly available.

Associated publication (forthcoming):
Brinkmann, F., Hoyer, A., Hogg, A., Picinali, L., Geronazzo, M., & Weinzierl, S. (2026). Listener Acoustic Personalisation Challenge LAP24: Perceptual Evaluation of the HRTF Upsampling. Forum Acusticum 2026, Graz, Austria, September 2026.

Access the perceptual study, results, and complete HRTF dataset on GitHub

Workshop

The LAP Challenge workshop and award ceremony was hosted by the 32nd European Signal Processing Conference (EUSIPCO 24) on August 29, 2024 – in Lyon, France.

Detailed program: Thursday 29th August, 16:10-17:50 (GMT+2), Room Saint Clair 4

16:10 – 16:20 Welcome and Motivation for the Listener Acoustic Personalization Challenge 2024 Aidan Hogg and Michele Geronazzo

16:20 – 17:40 Main Session

16:20 – 17:00 Task 1: HRTF normalisation for merging different HRTF datasets

16:20 – 16:25: Task 1 Overview and Rules

16:25 – 16:45: Talk from Task 1 Winners: Normalization of Head-Related Transfer Functions Based on Neural Networks. Jiale Zhao, Dingding Yao, Zelin Qiu, Chengzhong Wang, and Junfeng Li

16:45 – 17:00: Task 1 Full Results and Discussion

17:00 – 17:40 Task 2: Spatial upsampling for obtaining a high-spatial-resolution HRTF from a very low number of directions

17:00 – 17:05: Task 2 Overview and Rules

17:05 – 17:25: Talk from Task 2 Winners: Retrieval-Augmented Neural Field for HRTF Upsampling and Personalization. Yoshiki Masuyama, Gordon Wichern, Francois G. Germain, Christopher Ick, and Jonathan Le Roux

17:25 – 17:40: Task 2 Full Results and Discussion

17:40 – 17:50 Award Ceremony and Closing

Task description documents

The documents below outline the complete description for each task.

The evaluation code is also publicly available here:

Submissions

To submit your solutions for the LAP Challenge tasks, fill out the forms below:

Key Dates

  • Task specifics released: March 27, 2024
  • Evaluation code released: April 4, 2024
  • Submission deadline: July 1, 2024
  • Award ceremony: August 29, 2024

Editorial aspects

Top-ranked solutions will be invited to submit a paper describing their method and result to be published in the IEEE Open Journal of Signal Processing (OJ-SP), a fully open-access publication of the IEEE Signal Processing Society, with a scope encompassing the full range of technical activities of the Society. Article processing charge (APC) waivers will be also available upon request.

Since the challenge provides original data and evaluation processes, participants also have the flexibility to submit already published solutions.

Awards

Winners of the two tasks will be invited to participate and reimbursed for the registration fee to EUSIPCO24 and, until available funds are reached, for travel and accommodation.

Organisers

Chair: Michele Geronazzo, University of Padova, IT, and Imperial College London, UK
Co-chair: Lorenzo Picinali, Imperial College London, UK

Chair of the Implementation: Roberto Barumerli, University of Verona, IT,
Chair of the Web Site and Dissemination: Aidan Hogg, Queen Mary University of London, UK

Fabian Brinkmann, Technische Universität Berlin, DE
Glen McLachlan, University of Antwerp, BE
Stavros Ntalampiras, University of Milan, IT
Johan Pauwels, Queen Mary University of London, UK
Katarina Poole, Imperial College London, UK
Rapolas Daugintis, Imperial College London, UK


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