From phonemes to images: levels of representation in a recurrent neural model of visually-grounded language learning

11 October 2016

Papers citing "From phonemes to images: levels of representation in a recurrent neural model of visually-grounded language learning"

11 / 11 papers shown

Title
Towards visually prompted keyword localisation for zero-resource spoken languages Leanne Nortje Herman Kamper 29 6 0 12 Oct 2022
Word Segmentation on Discovered Phone Units with Dynamic Programming and Self-Supervised Scoring Herman Kamper 34 25 0 24 Feb 2022
Keyword localisation in untranscribed speech using visually grounded speech models Kayode Olaleye Dan Oneaţă Herman Kamper 32 7 0 02 Feb 2022
Probing artificial neural networks: insights from neuroscience Anna A. Ivanova John Hewitt Noga Zaslavsky 24 16 0 16 Apr 2021
Visualisation and 'diagnostic classifiers' reveal how recurrent and recursive neural networks process hierarchical structure Dieuwke Hupkes Sara Veldhoen Willem H. Zuidema 24 274 0 28 Nov 2017
Semantic speech retrieval with a visually grounded model of untranscribed speech Herman Kamper Gregory Shakhnarovich Karen Livescu 29 53 0 05 Oct 2017
Imagination improves Multimodal Translation Desmond Elliott Ákos Kádár 29 136 0 11 May 2017
What do Neural Machine Translation Models Learn about Morphology? Yonatan Belinkov Nadir Durrani Fahim Dalvi Hassan Sajjad James R. Glass 61 410 0 11 Apr 2017
Visually grounded learning of keyword prediction from untranscribed speech Herman Kamper Shane Settle Gregory Shakhnarovich Karen Livescu 19 63 0 23 Mar 2017
Representations of language in a model of visually grounded speech signal Grzegorz Chrupała Lieke Gelderloos A. Alishahi 41 131 0 07 Feb 2017
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 269 2,552 0 25 Jan 2016