16 accepted papers
Studies have shown that in noisy acoustic environments, providing binaural signals to the user of an assistive listening device may improve speech intelligibility and spatial awareness. This paper presents a binaural speech enhancement method using a complex convolutional neural network with an enco…
Speech enhancement in hearing aids (HAs) can take advantage of a wireless remote microphone (RM) having a better signal-to-noise ratio than the HA microphones. However, using the RM effectively is complicated by the time delay between the acoustic and wireless signals. Methods in the literature assu…
Distributed Microphone Arrays (DMAs) present many challenges with respect to centralized microphone arrays. An important requirement of applications on these arrays is handling a variable number of input channels. We consider the use of Graph Neural Networks (GNNs) as a solution to this challenge. W…
Intelligibility metrics are a fast way to determine how comprehensible a target signal is in a noisy situation. Most metrics however rely on having a clean reference signal for computation and are not adapted to live recordings. In this paper the deep correlation modified binaural short time objecti…
Multichannel acoustic signal processing is predicated on the fact that the interchannel relationships between the received signals can be exploited to infer information about the acoustic scene. Recently there has been increasing interest in algorithms which are applicable in dynamic scenes, where t…
The use of spatial information in multichannel speech enhancement methods is well established but information associated with the temporal evolution of speech is less commonly exploited. Speech signals can be modelled using an autoregressive process in the time-frequency modulation domain, and Kalma…
A method for room identification is proposed based on the reverberation properties of multichannel speech recordings. The approach exploits the dependence of spectral decay statistics on the reverberation time of a room. The average negative-side variance within 1/3-octave bands is proposed as the i…
In room acoustics, under-modelled multichannel blind system identification (BSI) aims to estimate the early part of the room impulse responses (RIRs), and it can be widely used in applications such as speaker localization, room geometry identification and beamforming based speech dereverberation. In…
Blur in images, caused by camera motion with an open shutter, is usually thought of as a problem. The algorithm described in this paper shows instead that it is possible to use the blur caused by the integration of light rays at different locations along a moving camera trajectory to extract informa…
It is known that applying a time-frequency binary mask to very noisy speech can improve its intelligibility but results in poor perceptual quality. In this paper we propose a new approach to applying a binary mask that combines the intelligibility gains of conventional binary masking with the percep…
Accurate interpolation of the array manifold is an important first step for the acoustic simulation of rapidly moving microphone arrays. Spherical harmonic domain interpolation has been proposed and well studied in the context of head-related transfer functions but has focussed on perceptual, rather…
It is known that the information required for the intelligibility of a speech signal is distributed non-uniformly in time. In this paper we propose WSTOI, a modified version of STOI, a speech intelligibility metric. With WSTOI the contribution of each time-frequency cell is weighted by an estimate o…
In this paper, we propose a minimum mean square error spectral estimator for clean speech spectral amplitudes that uses a Kalman filter to model the temporal dynamics of the spectral amplitudes in the modulation domain. Using a two-parameter Gamma distribution to model the prior distribution of the…
It is known that the intelligibility of noisy speech can be improved by applying a binary-valued gain mask to a time-frequency representation of the speech. We present the SOBM, an oracle binary mask that maximises STOI, an objective speech intelligibility metric. We show how to determine the SOBM f…
The reverberation of an acoustic channel can be characterised by two frequency-dependent parameters: the reverberation time and the direct-to-reverberant energy ratio. This paper presents an algorithm for blindly determining these parameters from a single-channel speech signal. The algorithm uses an…
In this paper, we present a novel speaker change detection and speaker diarization algorithm using spatial information in the form of features derived from estimated Room Impulse Response (RIR)s. A blind system identification approach is used to obtain an estimate of the RIRs, from which the C5 feat…