Jacob Sandakly — accepted AI-conference papers

2025

BinauralFlow: A Causal and Streamable Approach for High-Quality Binaural Speech Synthesis with Flow Matching Models

Susan Liang, Dejan Markovic, Israel D. Gebru, Steven Krenn, Todd Keebler, Jacob Sandakly +4

ICML 2025poster

Binaural rendering aims to synthesize binaural audio that mimics natural hearing based on a mono audio and the locations of the speaker and listener. Although many methods have been proposed to solve this problem, they struggle with rendering quality and streamable inference. Synthesizing high-qual…

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2023

Sounding Bodies: Modeling 3D Spatial Sound of Humans Using Body Pose and Audio

Xudong XU, Dejan Markovic, Jacob Sandakly, Todd Keebler, Steven Krenn, Alexander Richard

NeurIPS 2023spotlight

While 3D human body modeling has received much attention in computer vision, modeling the acoustic equivalent, i.e. modeling 3D spatial audio produced by body motion and speech, has fallen short in the community. To close this gap, we present a model that can generate accurate 3D spatial audio for f…

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