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Visual Grounding of Inter-lingual Word-Embeddings

arXiv 2209.03714 ↗First posted 8 Sep 2022cs.CLcited by 0

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Abstract (arXiv)

Visual grounding of Language aims at enriching textual representations of language with multiple sources of visual knowledge such as images and videos. Although visual grounding is an area of intense research, inter-lingual aspects of visual grounding have not received much attention. The present study investigates the inter-lingual visual grounding of word embeddings. We propose an implicit alignment technique between the two spaces of vision and language in which inter-lingual textual information interacts in order to enrich pre-trained textual word embeddings. We focus on three languages in our experiments, namely, English, Arabic, and German. We obtained visually grounded vector representations for these languages and studied whether visual grounding on one or multiple languages improved the performance of embeddings on word similarity and categorization benchmarks. Our experiments suggest that inter-lingual knowledge improves the performance of grounded embeddings in similar languages such as German and English. However, inter-lingual grounding of German or English with Arabic led to a slight degradation in performance on word similarity benchmarks. On the other hand, we observed an opposite trend on categorization benchmarks where Arabic had the most improvement on English. In the discussion section, several reasons for those findings are laid out. We hope that our experiments provide a baseline for further research on inter-lingual visual grounding.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 15 of its 40 references that are in the map. First posted on arXiv 8 Sep 2022.

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References · 15

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
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  3. 2019Cross-lingual Language Model Pretrainingcited by 1,090
  4. 2017Word Translation Without Parallel Datacited by 487
  5. 2014SimLex-999: Evaluating Semantic Models with (Genuine) Similarity Estimationcited by 172
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  7. 2022Towards a Cleaner Document-Oriented Multilingual Crawled Corpuscited by 143
  8. 2021UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-trainingcited by 64
  9. 2016SimVerb-3500: A Large-Scale Evaluation Set of Verb Similaritycited by 44
  10. 2021Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalancited by 26
  11. 2020Learning to Scale Multilingual Representations for Vision-Language Taskscited by 22
  12. 2021Learning Zero-Shot Multifaceted Visually Grounded Word Embeddings via Multi-Task Trainingcited by 8
3 more
  1. 2019Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Taskcited by 6
  2. 2022Language with Vision: a Study on Grounded Word and Sentence Embeddingscited by 5
  3. 2017Better Text Understanding Through Image-To-Text Transfercited by 2

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