1 code implementation • 22 Aug 2023 • Eyal Hanania, Ilya Volovik, Lilach Barkat, Israel Cohen, Moti Freiman
We compared PCMC-T1 to baseline deep-learning-based image registration approaches using a 5-fold experimental setup on a publicly available dataset of 210 patients.
no code implementations • 27 Jun 2022 • Gregory Ciccarelli, Jarred Barber, Arun Nair, Israel Cohen, Tao Zhang
We review current solutions and technical challenges for automatic speech recognition, keyword spotting, device arbitration, speech enhancement, and source localization in multidevice home environments to provide context for the INTERSPEECH 2022 special session, "Challenges and opportunities for signal processing and machine learning for multiple smart devices".
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 29 Jun 2021 • 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.
no code implementations • 25 Jun 2021 • 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 the spectral domain.
no code implementations • 25 Jun 2021 • Amir Ivry, Baruch Berdugo, Israel Cohen
A deep neural network, which is trained to separate speech from non-speech frames, is obtained by concatenating the decoder to the encoder, resembling the known Diffusion nets architecture.
no code implementations • 25 Jun 2021 • Amir Ivry, Israel Cohen, Baruch Berdugo
Second, the network is succeeded by a standard adaptive linear filter that constantly tracks the echo path between the loudspeaker output and the microphone.
no code implementations • 25 Jun 2021 • Amir Ivry, Israel Cohen, Baruch Berdugo
To mitigate this mismatch between training data and real data, we simulate an augmented training set that contains nearly five million utterances.
1 code implementation • 18 Aug 2017 • Gal Mishne, Ronen Talmon, Israel Cohen, Ronald R. Coifman, Yuval Kluger
Often the data is such that the observations do not reside on a regular grid, and the given order of the features is arbitrary and does not convey a notion of locality.
no code implementations • 11 Apr 2016 • David Dov, Ronen Talmon, Israel Cohen
In this paper, we address the problem of multiple view data fusion in the presence of noise and interferences.
no code implementations • 25 Jun 2015 • Gal Mishne, Uri Shaham, Alexander Cloninger, Israel Cohen
In this paper, we propose a manifold learning algorithm based on deep learning to create an encoder, which maps a high-dimensional dataset and its low-dimensional embedding, and a decoder, which takes the embedded data back to the high-dimensional space.