Learning Language-Independent Representations of Verbs and Adjectives from Multimodal Retrieval

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

Standard

Learning Language-Independent Representations of Verbs and Adjectives from Multimodal Retrieval. / Hansen, Victor Petren Bach; Sogaard, Anders.

Proceedings - 14th International Conference on Signal-Image Technology and Internet Based Systems, SITIS. IEEE, 2019. s. 427-434.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

Harvard

Hansen, VPB & Sogaard, A 2019, Learning Language-Independent Representations of Verbs and Adjectives from Multimodal Retrieval. i Proceedings - 14th International Conference on Signal-Image Technology and Internet Based Systems, SITIS. IEEE, s. 427-434, 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018, Las Palmas de Gran Canaria, Spanien, 26/11/2018. https://doi.org/10.1109/SITIS.2018.00072

APA

Hansen, V. P. B., & Sogaard, A. (2019). Learning Language-Independent Representations of Verbs and Adjectives from Multimodal Retrieval. I Proceedings - 14th International Conference on Signal-Image Technology and Internet Based Systems, SITIS (s. 427-434). IEEE. https://doi.org/10.1109/SITIS.2018.00072

Vancouver

Hansen VPB, Sogaard A. Learning Language-Independent Representations of Verbs and Adjectives from Multimodal Retrieval. I Proceedings - 14th International Conference on Signal-Image Technology and Internet Based Systems, SITIS. IEEE. 2019. s. 427-434 https://doi.org/10.1109/SITIS.2018.00072

Author

Hansen, Victor Petren Bach ; Sogaard, Anders. / Learning Language-Independent Representations of Verbs and Adjectives from Multimodal Retrieval. Proceedings - 14th International Conference on Signal-Image Technology and Internet Based Systems, SITIS. IEEE, 2019. s. 427-434

Bibtex

@inproceedings{00a0e191d4864d6dbf69dc26676c02fb,
title = "Learning Language-Independent Representations of Verbs and Adjectives from Multimodal Retrieval",
abstract = "This paper presents a simple modification to previous work on learning cross-lingual, grounded word representations from image-word pairs that, unlike previous work, is robust across different parts of speech, e.g., able to find the translation of the adjective 'social' relying only on image features associated with its translation candidates. Our method does not rely on black-box image search engines or any direct cross-lingual supervision. We evaluate our approach on English-German and English-Japanese word alignment, as well as on existing English-German bilingual dictionary induction datasets.",
keywords = "Computer vision, Cross-lingual learning, Distributional semantics, Multi-modal retrieval, Natural language processing",
author = "Hansen, {Victor Petren Bach} and Anders Sogaard",
year = "2019",
doi = "10.1109/SITIS.2018.00072",
language = "English",
pages = "427--434",
booktitle = "Proceedings - 14th International Conference on Signal-Image Technology and Internet Based Systems, SITIS",
publisher = "IEEE",
note = "14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018 ; Conference date: 26-11-2018 Through 29-11-2018",

}

RIS

TY - GEN

T1 - Learning Language-Independent Representations of Verbs and Adjectives from Multimodal Retrieval

AU - Hansen, Victor Petren Bach

AU - Sogaard, Anders

PY - 2019

Y1 - 2019

N2 - This paper presents a simple modification to previous work on learning cross-lingual, grounded word representations from image-word pairs that, unlike previous work, is robust across different parts of speech, e.g., able to find the translation of the adjective 'social' relying only on image features associated with its translation candidates. Our method does not rely on black-box image search engines or any direct cross-lingual supervision. We evaluate our approach on English-German and English-Japanese word alignment, as well as on existing English-German bilingual dictionary induction datasets.

AB - This paper presents a simple modification to previous work on learning cross-lingual, grounded word representations from image-word pairs that, unlike previous work, is robust across different parts of speech, e.g., able to find the translation of the adjective 'social' relying only on image features associated with its translation candidates. Our method does not rely on black-box image search engines or any direct cross-lingual supervision. We evaluate our approach on English-German and English-Japanese word alignment, as well as on existing English-German bilingual dictionary induction datasets.

KW - Computer vision

KW - Cross-lingual learning

KW - Distributional semantics

KW - Multi-modal retrieval

KW - Natural language processing

UR - http://www.scopus.com/inward/record.url?scp=85065904244&partnerID=8YFLogxK

U2 - 10.1109/SITIS.2018.00072

DO - 10.1109/SITIS.2018.00072

M3 - Article in proceedings

AN - SCOPUS:85065904244

SP - 427

EP - 434

BT - Proceedings - 14th International Conference on Signal-Image Technology and Internet Based Systems, SITIS

PB - IEEE

T2 - 14th International Conference on Signal Image Technology and Internet Based Systems, SITIS 2018

Y2 - 26 November 2018 through 29 November 2018

ER -

ID: 223253166