Add to ORKGRecent work has revealed the potential of using visual representations for bilingual lexicon learning (BLL). Such image-based BLL methods, however, still fall short of linguistic approaches. In this paper, we propose a simple yet effective multimodal approach that learns bilingual semantic representations that fuse linguistic and visual input. These new bilingual multi-modal embeddings display significant performance gains in the BLL task for three language pairs on two benchmarking test sets, outperforming linguistic-only BLL models using three different types of state-of-the-art bilingual word embeddings, as well as visual-only BLL models.status: publishe
We introduce bilingual word embeddings: semantic embeddings associated across two languages in the c...
This paper is concerned with the task of bilingual lexicon induction using image-based features. By ...
© 2017 Association for Computational Linguistics. We study the problem of bilingual lexicon inductio...
Recent work has revealed the potential of using visual representations for bilingual lexicon learnin...
Recent work has revealed the potential of using visual representations for bilingual lexicon learnin...
Bilingual lexicon induction, translating words from the source language to the target language, is a...
We propose a new model for learning bilingual word representations from non-parallel document-aligne...
Existing vision-language methods typically support two languages at a time at most. In this paper, w...
We propose a new model for learning bilingual word representations from non-parallel document-aligne...
Existing vision-language methods typically support two languages at a time at most. In this paper, w...
We propose a simple yet effective approach to learning bilingual word embeddings (BWEs) from non-par...
We explore methods to enrich the diversity of captions associated with pictures for learning improve...
Multimodal models have been proven to outperform text-based models on learning semantic word represe...
Recent work in learning bilingual repre-sentations tend to tailor towards achiev-ing good performanc...
Typically it is seen that multimodal neural machine translation (MNMT) systems trained on a combinat...
We introduce bilingual word embeddings: semantic embeddings associated across two languages in the c...
This paper is concerned with the task of bilingual lexicon induction using image-based features. By ...
© 2017 Association for Computational Linguistics. We study the problem of bilingual lexicon inductio...
Recent work has revealed the potential of using visual representations for bilingual lexicon learnin...
Recent work has revealed the potential of using visual representations for bilingual lexicon learnin...
Bilingual lexicon induction, translating words from the source language to the target language, is a...
We propose a new model for learning bilingual word representations from non-parallel document-aligne...
Existing vision-language methods typically support two languages at a time at most. In this paper, w...
We propose a new model for learning bilingual word representations from non-parallel document-aligne...
Existing vision-language methods typically support two languages at a time at most. In this paper, w...
We propose a simple yet effective approach to learning bilingual word embeddings (BWEs) from non-par...
We explore methods to enrich the diversity of captions associated with pictures for learning improve...
Multimodal models have been proven to outperform text-based models on learning semantic word represe...
Recent work in learning bilingual repre-sentations tend to tailor towards achiev-ing good performanc...
Typically it is seen that multimodal neural machine translation (MNMT) systems trained on a combinat...
We introduce bilingual word embeddings: semantic embeddings associated across two languages in the c...
This paper is concerned with the task of bilingual lexicon induction using image-based features. By ...
© 2017 Association for Computational Linguistics. We study the problem of bilingual lexicon inductio...