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Emmanuel Dupoux

40 papers hereh-index 6819.2k citations286 works total

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

author position
  • sole author1
  • middle author12
  • last author25

Across the 38 of 40 papers where every author was matched, so the position is known.

fields
  • cs.CL26
  • eess.AS7
  • cs.MA2
  • cs.SD2
  • cs.AI1
  • cs.CV1
Homepage
same name
  • Emmanuel Dupoux — 35 papers, h 20
  • Emmanuel Dupoux — 5 papers, h 4
  • Emmanuel Dupoux — 4 papers, h 3
  • Emmanuel Dupoux — 3 papers, h 3
  • Emmanuel Dupoux — 2 papers, h 4
  • Emmanuel Dupoux — 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
20162022
most citedData Augmenting Contrastive Learning of Speech Representations in the Time Domain

93 citations · 190 across the 13 of their papers we have counts for

collaborators
Showing 2017Show all

4 papers · 1 filter

cs.CL2017★ 1 cited

Are words easier to learn from infant- than adult-directed speech? A quantitative corpus-based investigation

Adriana Guevara-Rukoz, Alejandrina Cristia, Bogdan Ludusan +4

We investigate whether infant-directed speech (IDS) could facilitate word form learning when compared to adult-directed speech (ADS). To study this, we examine the distribution of…

cs.CL2017

The Zero Resource Speech Challenge 2017

Ewan Dunbar, Xuan Nga Cao, Juan Benjumea +5

We describe a new challenge aimed at discovering subword and word units from raw speech. This challenge is the followup to the Zero Resource Speech Challenge 2015. It aims at const…

cs.CL2017

Learning Filterbanks from Raw Speech for Phone Recognition

Neil Zeghidour, Nicolas Usunier, Iasonas Kokkinos +3

We train a bank of complex filters that operates on the raw waveform and is fed into a convolutional neural network for end-to-end phone recognition. These time-domain filterbanks…

cs.CL2017

Learning weakly supervised multimodal phoneme embeddings

Rahma Chaabouni, Ewan Dunbar, Neil Zeghidour +1

Recent works have explored deep architectures for learning multimodal speech representation (e.g. audio and images, articulation and audio) in a supervised way. Here we investigate…

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