164 citations · 164 across the 3 of their papers we have counts for
7 papers
Self-Supervised Contrastive Learning for Unsupervised Phoneme Segmentation
Felix Kreuk, Joseph Keshet, Yossi Adi
We propose a self-supervised representation learning model for the task of unsupervised phoneme boundary detection. The model is a convolutional neural network that operates direct…
Phoneme Boundary Detection using Learnable Segmental Features
Felix Kreuk, Yaniv Sheena, Joseph Keshet +1
Phoneme boundary detection plays an essential first step for a variety of speech processing applications such as speaker diarization, speech science, keyword spotting, etc. In this…
Hide and Speak: Towards Deep Neural Networks for Speech Steganography
Felix Kreuk, Yossi Adi, Bhiksha Raj +2
Steganography is the science of hiding a secret message within an ordinary public message, which is referred to as Carrier. Traditionally, digital signal processing techniques, suc…
Out-of-Distribution Detection using Multiple Semantic Label Representations
Gabi Shalev, Yossi Adi, Joseph Keshet
Deep Neural Networks are powerful models that attained remarkable results on a variety of tasks. These models are shown to be extremely efficient when training and test data are dr…
Fooling End-to-end Speaker Verification by Adversarial Examples
Felix Kreuk, Yossi Adi, Moustapha Cisse +1
Automatic speaker verification systems are increasingly used as the primary means to authenticate costumers. Recently, it has been proposed to train speaker verification systems us…
Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring
Yossi Adi, Carsten Baum, Moustapha Cisse +2
Deep Neural Networks have recently gained lots of success after enabling several breakthroughs in notoriously challenging problems. Training these networks is computationally expen…