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Joseph Keshet

Electrical and Computer Engineering, Technion--Israel Institute of Technology, Israel

31 papers hereh-index 316.4k citations106 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author6
  • last author24

Across the 30 of 31 papers where every author was matched, so the position is known.

fields
  • eess.AS9
  • cs.LG8
  • cs.CL4
  • cs.SD4
  • stat.ML3
  • cs.AI2
affiliations
  • Electrical and Computer Engineering, Technion--Israel Institute of Technology, Israel
Homepage
same name
  • Joseph Keshet — 20 papers, h 6
  • Joseph Keshet — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20112023
most citedHoudini: Fooling Deep Structured Prediction Models

164 citations · 430 across the 25 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2017

Automatic Measurement of Pre-aspiration

Yaniv Sheena, Míša Hejná, Yossi Adi +1

Pre-aspiration is defined as the period of glottal friction occurring in sequences of vocalic/consonantal sonorants and phonetically voiceless obstruents. We propose two machine le…

cs.CL2017

Learning Similarity Functions for Pronunciation Variations

Einat Naaman, Yossi Adi, Joseph Keshet

A significant source of errors in Automatic Speech Recognition (ASR) systems is due to pronunciation variations which occur in spontaneous and conversational speech. Usually ASR sy…

cs.CL2016

Domain Adaptation For Formant Estimation Using Deep Learning

Yehoshua Dissen, Joseph Keshet, Jacob Goldberger +1

In this paper we present a domain adaptation technique for formant estimation using a deep network. We first train a deep learning network on a small read speech dataset. We then f…

cs.CL2016

Sequence Segmentation Using Joint RNN and Structured Prediction Models

Yossi Adi, Joseph Keshet, Emily Cibelli +1

We describe and analyze a simple and effective algorithm for sequence segmentation applied to speech processing tasks. We propose a neural architecture that is composed of two modu…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.