166 citations · 378 across the 12 of their papers we have counts for
6 papers · 1 filter
Objective Metrics to Evaluate Residual-Echo Suppression During Double-Talk
Amir Ivry, Israel Cohen, Baruch Berdugo
Human subjective evaluation is optimal to assess speech quality for human perception. The recently introduced deep noise suppression mean opinion score (DNSMOS) metric was shown to…
Convolutional Sparse Coding Fast Approximation with Application to Seismic Reflectivity Estimation
Deborah Pereg, Israel Cohen, Anthony A. Vassiliou
In sparse coding, we attempt to extract features of input vectors, assuming that the data is inherently structured as a sparse superposition of basic building blocks. Similarly, ne…
Voice Activity Detection for Transient Noisy Environment Based on Diffusion Nets
Amir Ivry, Baruch Berdugo, Israel Cohen
We address voice activity detection in acoustic environments of transients and stationary noises, which often occur in real life scenarios. We exploit unique spatial patterns of sp…
Nonlinear Acoustic Echo Cancellation with Deep Learning
Amir Ivry, Israel Cohen, Baruch Berdugo
We propose a nonlinear acoustic echo cancellation system, which aims to model the echo path from the far-end signal to the near-end microphone in two parts. Inspired by the physica…
Deep Residual Echo Suppression with A Tunable Tradeoff Between Signal Distortion and Echo Suppression
Amir Ivry, Israel Cohen, Baruch Berdugo
In this paper, we propose a residual echo suppression method using a UNet neural network that directly maps the outputs of a linear acoustic echo canceler to the desired signal in…
Evaluation of Deep-Learning-Based Voice Activity Detectors and Room Impulse Response Models in Reverberant Environments
Amir Ivry, Israel Cohen, Baruch Berdugo
State-of-the-art deep-learning-based voice activity detectors (VADs) are often trained with anechoic data. However, real acoustic environments are generally reverberant, which caus…