Related papers: Binaural rendering from microphone array signals o…

Knowing the room geometry may be very beneficial for many audio applications, including sound reproduction, acoustic scene analysis, and sound source localization. Room geometry inference (RGI) deals with the problem of reflector…

Speech separation with several speakers is a challenging task because of the non-stationarity of the speech and the strong signal similarity between interferent sources. Current state-of-the-art solutions can separate well the different…

A binaural rendering framework for personal sound zones (PSZs) is proposed to enable multiple head-tracked listeners to receive fully independent stereo audio programs. Current PSZ systems typically rely on monophonic rendering and…

In this paper, we propose a novel separation system for extracting two speech signals from two microphone recordings. Our system combines the blind source separation technique with cepstral smoothing of binary time-frequency masks. The last…

This paper proposes a neural network based speech separation method using spatially distributed microphones. Unlike with traditional microphone array settings, neither the number of microphones nor their spatial arrangement is known in…

Binaural stereo audio is recorded by imitating the way the human ear receives sound, which provides people with an immersive listening experience. Existing approaches leverage autoencoders and directly exploit visual spatial information to…

Sound propagation in the ocean is considered. We demonstrate a novel algorithm for full wavefield reconstruction using pointwise measurements by means of a vertical array. The algorithm is based on the so-called discrete variable…

Conventional sampling and interpolation commonly rely on discrete measurements. In this paper, we develop a theoretical framework for extrapolation of signals in higher dimensions from knowledge of the continuous waveform on bounded…

We investigate synthesis of a large effective aperture using a sparse array of subarrays. We employ a multi-objective optimization framework for placement of subarrays within a prescribed area dictated by form factor constraints, trading…

The conventional room geometry blind inference techniques with acoustic signals are conducted based on the prior knowledge of the environment, such as the room impulse response (RIR) or the sound source position, which will limit its…

In this contribution, we consider MUltiple SIgnal Classification (MUSIC)-type algorithm for a non-iterative microwave imaging of small and arbitrary shaped extended anomalies located in a homogeneous media from scattering matrix whose…

Human and/or asset tracking using an attached sensor units helps understand their activities. Most common indoor localization methods for human tracking technologies require expensive infrastructures, deployment and maintenance. To overcome…

Spatial sound field interpolation relies on suitable models to both conform to available measurements and predict the sound field in the domain of interest. A suitable model can be difficult to determine when the spatial domain of interest…

In this paper, we propose an effective and robust method for acoustic scene analysis based on spatial information extracted from partially synchronized and/or closely located distributed microphones. In the proposed method, to extract…

In this paper, we propose to simultaneously estimate all the sampling rate offsets (SROs) of multiple devices. In a distributed microphone array, the SRO is inevitable, which deteriorates the performance of array signal processing. Most of…

The characterization of a binary function by partial frequency information is considered. We show that it is possible to reconstruct binary signals from incomplete frequency measurements via the solution of a simple linear optimization…

Ambisonics is a method for capturing and rendering a sound field accurately, assuming that the acoustics of the playback room does not significantly influence the sound field. However, in practice, the acoustics of the playback room may…

A deep learning model is proposed for reconstructing 2D dielectric breast images from time-domain signals. Unlike existing learning models that employ a fixed antenna array, where input data consists solely of measurements, the proposed…

This paper addresses the problem of localizing audio sources using binaural measurements. We propose a supervised formulation that simultaneously localizes multiple sources at different locations. The approach is intrinsically efficient…

Audio zooming, a signal processing technique, enables selective focusing and enhancement of sound signals from a specified region, attenuating others. While traditional beamforming and neural beamforming techniques, centered on creating a…