# Models of Visually Grounded Speech Signal Pay Attention To Nouns: a Bilingual Experiment on English and Japanese

arXiv: https://arxiv.org/abs/1902.03052 · HTML: https://mlsanity.com/paper/1902.03052/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Feb 2019.

## Built on by (most cited first, 13 of 13)

- [Self-Supervised Speech Representation Learning: A Review](https://mlsanity.com/paper/2205.10643/) (2022)
- [Visually grounded models of spoken language: A survey of datasets, architectures and evaluation techniques](https://mlsanity.com/paper/2104.13225/) (2021)
- [Attention-Based Keyword Localisation in Speech using Visual Grounding](https://mlsanity.com/paper/2106.08859/) (2021)
- [Can phones, syllables, and words emerge as side-products of cross-situational audiovisual learning? -- A computational investigation](https://mlsanity.com/paper/2109.14200/) (2021)
- [Syllable Discovery and Cross-Lingual Generalization in a Visually Grounded, Self-Supervised Speech Model](https://mlsanity.com/paper/2305.11435/) (2023)
- [M-SpeechCLIP: Leveraging Large-Scale, Pre-Trained Models for Multilingual Speech to Image Retrieval](https://mlsanity.com/paper/2211.01180/) (2022)
- [Cascaded Multilingual Audio-Visual Learning from Videos](https://mlsanity.com/paper/2111.04823/) (2021)
- [Learning English with Peppa Pig](https://mlsanity.com/paper/2202.12917/) (2022)
- [Keyword localisation in untranscribed speech using visually grounded speech models](https://mlsanity.com/paper/2202.01107/) (2022)
- [ZR-2021VG: Zero-Resource Speech Challenge, Visually-Grounded Language Modelling track, 2021 edition](https://mlsanity.com/paper/2107.06546/) (2021)
- [Spoken ObjectNet: A Bias-Controlled Spoken Caption Dataset](https://mlsanity.com/paper/2110.07575/) (2021)
- [Computational modeling of early language learning from acoustic speech and audiovisual input without linguistic priors](https://mlsanity.com/paper/2603.08359/) (2026)
- [Mapping Written Words to Spoken Words in a Different Language Using Only Visual Grounding](https://mlsanity.com/paper/2608.26925/) (2026)

## Abstract (arXiv)

We investigate the behaviour of attention in neural models of visually grounded speech trained on two languages: English and Japanese. Experimental results show that attention focuses on nouns and this behaviour holds true for two very typologically different languages. We also draw parallels between artificial neural attention and human attention and show that neural attention focuses on word endings as it has been theorised for human attention. Finally, we investigate how two visually grounded monolingual models can be used to perform cross-lingual speech-to-speech retrieval. For both languages, the enriched bilingual (speech-image) corpora with part-of-speech tags and forced alignments are distributed to the community for reproducible research.