164 citations · 167 across the 8 of their papers we have counts for
15 papers
THOR: Threshold-Based Ranking Loss for Ordinal Regression
Tzeviya Sylvia Fuchs, Joseph Keshet
In this work, we present a regression-based ordinal regression algorithm for supervised classification of instances into ordinal categories. In contrast to previous methods, in thi…
Unsupervised Word Segmentation using K Nearest Neighbors
Tzeviya Sylvia Fuchs, Yedid Hoshen, Joseph Keshet
In this paper, we propose an unsupervised kNN-based approach for word segmentation in speech utterances. Our method relies on self-supervised pre-trained speech representations, an…
CNN-based Spoken Term Detection and Localization without Dynamic Programming
Tzeviya Sylvia Fuchs, Yael Segal, Joseph Keshet
In this paper, we propose a spoken term detection algorithm for simultaneous prediction and localization of in-vocabulary and out-of-vocabulary terms within an audio segment. The p…
Constant Random Perturbations Provide Adversarial Robustness with Minimal Effect on Accuracy
Bronya Roni Chernyak, Bhiksha Raj, Tamir Hazan +1
This paper proposes an attack-independent (non-adversarial training) technique for improving adversarial robustness of neural network models, with minimal loss of standard accuracy…
Redesigning the classification layer by randomizing the class representation vectors
Gabi Shalev, Gal-Lev Shalev, Joseph Keshet
Neural image classification models typically consist of two components. The first is an image encoder, which is responsible for encoding a given raw image into a representative vec…
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…