no code implementations • 29 Feb 2024 • Bar Shaybet, Anurag Kumar, Vladimir Tourbabin, Boaz Rafaely
Ambisonics, a popular format of spatial audio, is the spherical harmonic (SH) representation of the plane wave density function of a sound field.
no code implementations • 27 Feb 2024 • Yhonatan Gayer, Vladimir Tourbabin, Zamir Ben-Hur, Jacob Donley, Boaz Rafaely
In the rapidly evolving fields of virtual and augmented reality, accurate spatial audio capture and reproduction are essential.
no code implementations • 6 Jan 2024 • Vladimir Tourbabin, Boaz Rafaely
However, no theoretical framework for the design of these arrays has been presented.
no code implementations • 4 Jan 2024 • Vladimir Tourbabin, Boaz Rafaely
It is also demonstrated that by using the motion-based enhancement method it is possible to improve the direction of arrival estimation performance, as compared to that obtained when using a stationary array.
no code implementations • 21 Dec 2023 • Yogev Hadadi, Vladimir Tourbabin, Paul Calamia, Boaz Rafaely
Additionally, performance in terms of perception is investigated through a listening test.
no code implementations • 30 Nov 2023 • Sina Hafezi, Alastair H. Moore, Pierre H. Guiraud, Patrick A. Naylor, Jacob Donley, Vladimir Tourbabin, Thomas Lunner
(i) The first stage is a hybrid beamformer based on a dictionary of weights corresponding to a set of noise field models.
no code implementations • 22 Nov 2023 • Ami Berger, Vladimir Tourbabin, Jacob Donley, Zamir Ben-Hur, Boaz Rafaely
The capture and reproduction of spatial audio is becoming increasingly popular, with the mushrooming of applications in teleconferencing, entertainment and virtual reality.
no code implementations • 15 Mar 2023 • Sina Hafezi, Alastair H. Moore, Pierre Guiraud, Patrick A. Naylor, Jacob Donley, Vladimir Tourbabin, Thomas Lunner
A two-stage multi-channel speech enhancement method is proposed which consists of a novel adaptive beamformer, Hybrid Minimum Variance Distortionless Response (MVDR), Isotropic-MVDR (Iso), and a novel multi-channel spectral Principal Components Analysis (PCA) denoising.
1 code implementation • 9 Jul 2021 • Jacob Donley, Vladimir Tourbabin, Jung-Suk Lee, Mark Broyles, Hao Jiang, Jie Shen, Maja Pantic, Vamsi Krishna Ithapu, Ravish Mehra
In this work, we describe, evaluate and release a dataset that contains over 5 hours of multi-modal data useful for training and testing algorithms for the application of improving conversations for an AR glasses wearer.
Ranked #1 on Speech Enhancement on EasyCom