SONICOM HRTF Dataset part of Huawei challenge

The SONICOM HRTF Dataset is being used as the main data input for training the AI model used in an ‘Individual Head-Related Transfer Functions (HRTFs)’ competition organised by Huawei.

The objective of the competition is to develop a method to synthesize/reconstruct HRTFs based on pictures of the person’s ears, and the SONICOM HRTF dataset of 3D meshes, 2D pinna images and corresponding acoustically measured HRTFs is provided as the input for model training.

“It’s great to see our open-source SONICOM HRTF dataset being utilised in this way,” says Prof Lorenzo Picinali, SONICOM’s Coordinator based at Imperial College London. “We look forward to seeing the innovative solutions the teams who take part end up producing.”

The SONICOM HRTF Dataset includes different types of data measured from 200 subjects, including HRTFs, HpTFs, depth pictures and 3D models of subjects’ ears, heads and torsos, with further measurements ongoing. All of this data is open-source and freely accessible.

More details about how the dataset has been measured can be found in our Journal of Audio Engineering Society paper.

Take part in the competition

Registration for the competition closes on 30 November 2024, with solutions due by 4 December. Participants must be studying a BSc, MSc, or PhD in engineering, maths, computer science or another related field at a higher education institution in Europe or the UK in order to be eligible.

Top performing teams, up to 50 people, will then be invited to the final in Germany pitch their innovative solution in front of a Huawei Jury Panel for a chance to win prizes ranging from cash and travel and internship opportunities.

Find out more about the competition on the Huawei 2024 Munich Tech Arena website.