148 citations · 172 across the 22 of their papers we have counts for
24 papers
Subspace Hybrid MVDR Beamforming for Augmented Hearing
Sina Hafezi, Alastair H. Moore, Pierre H. Guiraud +4
Signal-dependent beamformers are advantageous over signal-independent beamformers when the acoustic scenario - be it real-world or simulated - is straightforward in terms of the nu…
Dual input neural networks for positional sound source localization
Eric Grinstein, Vincent W. Neo, Patrick A. Naylor
In many signal processing applications, metadata may be advantageously used in conjunction with a high dimensional signal to produce a desired output. In the case of classical Soun…
Graph neural networks for sound source localization on distributed microphone networks
Eric Grinstein, Mike Brookes, Patrick A. Naylor
Distributed Microphone Arrays (DMAs) present many challenges with respect to centralized microphone arrays. An important requirement of applications on these arrays is handling a v…
Long-term Conversation Analysis: Exploring Utility and Privacy
Francesco Nespoli, Jule Pohlhausen, Patrick A. Naylor +1
The analysis of conversations recorded in everyday life requires privacy protection. In this contribution, we explore a privacy-preserving feature extraction method based on input…
Two-Stage Voice Anonymization for Enhanced Privacy
Francesco Nespoli, Daniel Barreda, Joerg Bitzer +1
In recent years, the need for privacy preservation when manipulating or storing personal data, including speech , has become a major issue. In this paper, we present a system addre…
Subspace Hybrid Beamforming for Head-worn Microphone Arrays
Sina Hafezi, Alastair H. Moore, Pierre Guiraud +4
A two-stage multi-channel speech enhancement method is proposed which consists of a novel adaptive beamformer, Hybrid Minimum Variance Distortionless Response (MVDR), Isotropic-MVD…
Relative Acoustic Features for Distance Estimation in Smart-Homes
Francesco Nespoli, Daniel Barreda, Patrick A. Naylor
Any audio recording encapsulates the unique fingerprint of the associated acoustic environment, namely the background noise and reverberation. Considering the scenario of a room eq…
Binaural Speech Enhancement Using STOI-Optimal Masks
Vikas Tokala, Mike Brookes, Patrick A. Naylor
STOI-optimal masking has been previously proposed and developed for single-channel speech enhancement. In this paper, we consider the extension to the task of binaural speech enhan…
Spatial Processing Front-End For Distant ASR Exploiting Self-Attention Channel Combinator
Dushyant Sharma, Rong Gong, James Fosburgh +3
We present a novel multi-channel front-end based on channel shortening with theWeighted Prediction Error (WPE) method followed by a fixed MVDR beamformer used in combination with a…
Time-Frequency Analysis and Parameterisation of Knee Sounds for Non-invasive Detection of Osteoarthritis
Costas Yiallourides, Patrick A. Naylor
Objective: In this work the potential of non-invasive detection of knee osteoarthritis is investigated using the sounds generated by the knee joint during walking. Methods: The inf…
Detection of Glottal Closure Instants from Speech Signals: a Quantitative Review
Thomas Drugman, Mark Thomas, Jon Gudnason +2
The pseudo-periodicity of voiced speech can be exploited in several speech processing applications. This requires however that the precise locations of the Glottal Closure Instants…
The LOCATA Challenge: Acoustic Source Localization and Tracking
Christine Evers, Heinrich Loellmann, Heinrich Mellmann +4
The ability to localize and track acoustic events is a fundamental prerequisite for equipping machines with the ability to be aware of and engage with humans in their surrounding e…
Detecting Sound-Absorbing Materials in a Room from a Single Impulse Response using a CRNN
Constantinos Papayiannis, Christine Evers, Patrick A. Naylor
The materials of surfaces in a room play an important room in shaping the auditory experience within them. Different materials absorb energy at different levels. The level of absor…
Data Augmentation of Room Classifiers using Generative Adversarial Networks
Constantinos Papayiannis, Christine Evers, Patrick A. Naylor
The classification of acoustic environments allows for machines to better understand the auditory world around them. The use of deep learning in order to teach machines to discrimi…
End-to-End Classification of Reverberant Rooms using DNNs
Constantinos Papayiannis, Christine Evers, Patrick A. Naylor
Reverberation is present in our workplaces, our homes, concert halls and theatres. This paper investigates how deep learning can use the effect of reverberation on speech to classi…
Proceedings of the LOCATA Challenge Workshop -- a satellite event of IWAENC 2018
Heinrich W. Loellmann, Christine Evers, Alexander Schmidt +3
Algorithms for acoustic source localization and tracking provide estimates of the positional information about active sound sources in acoustic environments and are essential for a…
Acoustic Characterization of Environments (ACE) Challenge Results Technical Report
James Eaton, Nikolay D. Gaubitch, Alastair H. Moore +1
This document provides the results of the tests of acoustic parameter estimation algorithms on the Acoustic Characterization of Environments (ACE) Challenge Evaluation dataset whic…
Direct-to-Reverberant Ratio Estimation on the ACE Corpus Using a Two-channel Beamformer
James Eaton, Patrick A. Naylor
Direct-to-Reverberant Ratio (DRR) is an important measure for characterizing the properties of a room. The recently proposed DRR Estimation using a Null-Steered Beamformer (DENBE)…
Evaluating the Non-Intrusive Room Acoustics Algorithm with the ACE Challenge
Pablo Peso Parada, Dushyant Sharma, Toon van Waterschoot +1
We present a single channel data driven method for non-intrusive estimation of full-band reverberation time and full-band direct-to-reverberant ratio. The method extracts a number…
Reverberation time estimation on the ACE corpus using the SDD method
James Eaton, Patrick A. Naylor
Reverberation Time (T60) is an important measure for characterizing the properties of a room. The author's T60 estimation algorithm was previously tested on simulated data where th…
Proceedings of the ACE Challenge Workshop - a satellite event of IEEE-WASPAA (2015)
James Eaton, Nikolay D. Gaubitch, Alastair H. Moore +1
Several established parameters and metrics have been used to characterize the acoustics of a room. The most important are the Direct-To-Reverberant Ratio (DRR), the Reverberation T…
Source Coding in Networks with Covariance Distortion Constraints
Adel Zahedi, Jan Østergaard, Søren Holdt Jensen +2
We consider a source coding problem with a network scenario in mind, and formulate it as a remote vector Gaussian Wyner-Ziv problem under covariance matrix distortions. We define a…
Distributed Remote Vector Gaussian Source Coding for Wireless Acoustic Sensor Networks
Adel Zahedi, Jan Ostergaard, Soren Holdt Jensen +2
In this paper, we consider the problem of remote vector Gaussian source coding for a wireless acoustic sensor network. Each node receives messages from multiple nodes in the networ…
Distributed Remote Vector Gaussian Source Coding with Covariance Distortion Constraints
Adel Zahedi, Jan Ostergaard, Soren Holdt Jensen +2
In this paper, we consider a distributed remote source coding problem, where a sequence of observations of source vectors is available at the encoder. The problem is to specify the…