Eric Grinstein
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View article: Binaural Localization Model for Speech in Noise
Binaural Localization Model for Speech in Noise Open
Binaural acoustic source localization is important to human listeners for spatial awareness, communication and safety. In this paper, an end-to-end binaural localization model for speech in noise is presented. A lightweight convolutional r…
View article: Controlling the Parameterized Multi-channel Wiener Filter using a tiny neural network
Controlling the Parameterized Multi-channel Wiener Filter using a tiny neural network Open
Noise suppression and speech distortion are two important aspects to be balanced when designing multi-channel Speech Enhancement (SE) algorithms. Although neural network models have achieved state-of-the-art noise suppression, their non-li…
View article: Steered Response Power for Sound Source Localization: a tutorial review
Steered Response Power for Sound Source Localization: a tutorial review Open
In the last three decades, the Steered Response Power (SRP) method has been widely used for the task of Sound Source Localization (SSL), due to its satisfactory localization performance on moderately reverberant and noisy scenarios. Many w…
View article: Steered Response Power for Sound Source Localization: A Tutorial Review
Steered Response Power for Sound Source Localization: A Tutorial Review Open
In the last three decades, the Steered Response Power (SRP) method has been widely used for the task of Sound Source Localization (SSL), due to its satisfactory localization performance on moderately reverberant and noisy scenarios. Many w…
View article: The Neural-SRP method for positional sound source localization
The Neural-SRP method for positional sound source localization Open
Steered Response Power (SRP) is a widely used method for the task of sound source localization using microphone arrays, showing satisfactory localization performance on many practical scenarios. However, its performance is diminished under…
View article: Binaural Speech Enhancement Using Deep Complex Convolutional Transformer Networks
Binaural Speech Enhancement Using Deep Complex Convolutional Transformer Networks Open
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 met…
View article: Binaural Speech Enhancement Using Complex Convolutional Recurrent Networks
Binaural Speech Enhancement Using Complex Convolutional Recurrent Networks Open
From hearing aids to augmented and virtual reality devices, binaural speech enhancement algorithms have been established as state-of-the-art techniques to improve speech intelligibility and listening comfort. In this paper, we present an e…
View article: Dual input neural networks for positional sound source localization
Dual input neural networks for positional sound source localization Open
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 Sound Source Localization (SSL) algorithms, information from a …
View article: Dual input neural networks for positional sound source localization
Dual input neural networks for positional sound source localization Open
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 Sound Source Localization (SSL) algorithms, information from a …
View article: Graph neural networks for sound source localization on distributed microphone networks
Graph neural networks for sound source localization on distributed microphone networks Open
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 Gr…
View article: The Neural-SRP Method for Universal Robust Multi-source Tracking
The Neural-SRP Method for Universal Robust Multi-source Tracking Open
Neural networks have achieved state-of-the-art performance on the task of acoustic Direction-of-Arrival (DOA) estimation using microphone arrays. Neural models can be classified as end-to-end or hybrid, each class showing advantages and di…
View article: Audio Style Transfer
Audio Style Transfer Open
'Style transfer' among images has recently emerged as a very active research\ntopic, fuelled by the power of convolution neural networks (CNNs), and has\nbecome fast a very popular technology in social media. This paper investigates\nthe a…
View article: Audio style transfer
Audio style transfer Open
'Style transfer' among images has recently emerged as a very active research topic, fuelled by the power of convolution neural networks (CNNs), and has become fast a very popular technology in social media. This paper investigates the anal…