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Data · dataset · 2014

Learning Words from Images and Speech

Listed in DataCite

This paper explores the possibility to learn a semantically-relevant lexicon from images and speech only.

Description

For this, we train a multi-modal neural network working both on image fragments and on speech features, by learning an embedding in which images and content words that co-occur together are close. Making no assumption on the acoustic model, this paper shows promising results on how multi-modality could help word learning.

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Topics

Inferred from text
Audio 65% · Image 75%
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
DataCite10.6084/m9.figshare.127782212 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[modality].local:modality:audioenrichment · DataCitekeyword-concept-rules@1.0.0title+description (65%)
concepts[modality].local:modality:imageenrichment · DataCitekeyword-concept-rules@1.0.0title+description (75%)
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