Related papers: Ambisonics Super-Resolution Using A Waveform-Domai…
Ambisonics i.e., a full-sphere surround sound, is quintessential with 360-degree visual content to provide a realistic virtual reality (VR) experience. While 360-degree visual content capture gained a tremendous boost recently, the…
Learning from audio-visual data offers many possibilities to express correspondence between the audio and visual content, similar to the human perception that relates aural and visual information. In this work, we present a method for…
Large audio-language models have made rapid progress in recognizing what is present in an audio clip, but spatial audio-language understanding still lacks a clear task interface. A model must also decide where sound events occur, which…
This paper presents a physics-informed neural network (PINN) for modeling first-order Ambisonic (FOA) room impulse responses (RIRs). PINNs have demonstrated promising performance in sound field interpolation by combining the powerful…
This contribution introduces a dataset of 7th-order Ambisonic Room Impulse Responses (HOA-RIRs), created using the Image Source Method. By employing higher-order Ambisonics, our dataset enables precise spatial audio reproduction, a critical…
Advances in virtual reality have generated substantial interest in accurately reproducing and storing spatial audio in the higher order ambisonics (HOA) representation, given its rendering flexibility. Recent standardization for HOA…
Directional Audio Coding (DirAC) is a proven method for parametrically representing a 3D audio scene in B-format and is capable of reproducing it on arbitrary loudspeaker layouts. Although such a method seems well suited for low bitrate…
Deep learning-based direction-of-arrival (DoA) estimation has gained increasing popularity. A popular family of DoA estimation algorithms is beamforming methods, which operate by constructing a spatial filter that is applied to array…
Traditional video-to-audio generation techniques primarily focus on perspective video and non-spatial audio, often missing the spatial cues necessary for accurately representing sound sources in 3D environments. To address this limitation,…
The paper presents a method for improving spatial resolution of first-order ambisonic audio. The method is based on time/frequency decomposition of the audio with subsequent extraction of a directed plane wave from each frequency component.…
In the rapidly evolving fields of virtual and augmented reality, accurate spatial audio capture and reproduction are essential. For these applications, Ambisonics has emerged as a standard format. However, existing methods for encoding…
Spatial audio has become central to immersive applications such as VR/AR, cinema, and music. Existing generative audio models are largely limited to mono or stereo formats and cannot capture the full 3D localization cues available in…
The importance of the information in the direct sound to human perception of spatial sound sources is an ongoing research topic. The classification between direct sound and diffuse or reverberant sound forms the basis of numerous studies in…
Ambisonics encoding of microphone array signals can enable various spatial audio applications, such as virtual reality or telepresence, but it is typically designed for uniformly-spaced spherical microphone arrays. This paper proposes a…
Spatial audio is essential for enhancing the immersiveness of audio-visual experiences, yet its production typically demands complex recording systems and specialized expertise. In this work, we address a novel problem of generating…
Emerging wearable devices such as smartglasses and extended reality headsets demand high-quality spatial audio capture from compact, head-worn microphone arrays. Ambisonics provides a device-agnostic spatial audio representation by mapping…
Sound field decomposition predicts waveforms in arbitrary directions using signals from a limited number of microphones as inputs. Sound field decomposition is fundamental to downstream tasks, including source localization, source…
Recently, the Spherical Wavelet Framework (SWF) was proposed to combine the benefits of Ambisonics and Object-Based Audio (OBA) by utilising highly localised basis functions. SWF can enhance the sweet-spot area and reduce localisation blur…
Ambisonics is an established framework to capture, process, and reproduce spatial sound fields based on its spherical harmonics representation. We propose a generalization of conventional spherical ambisonics to the spheroidal coordinate…
This paper introduces SoundSculpt, a neural network designed to extract target sound fields from ambisonic recordings. SoundSculpt employs an ambisonic-in-ambisonic-out architecture and is conditioned on both spatial information (e.g.,…