SOTAVerified

Multimodal Machine Translation

Multimodal machine translation is the task of doing machine translation with multiple data sources - for example, translating "a bird is flying over water" + an image of a bird over water to German text.

( Image credit: Findings of the Third Shared Task on Multimodal Machine Translation )

Papers

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Showing 76–100 of 108 papers

TitleStatusHype
Supervised Visual Attention for Simultaneous Multimodal Machine Translation—0
The AFRL-Ohio State WMT18 Multimodal System: Combining Visual with Traditional—0
The AFRL-OSU WMT17 Multimodal Translation System: An Image Processing Approach—0
The Case for Evaluating Multimodal Translation Models on Text Datasets—0
The MeMAD Submission to the WMT18 Multimodal Translation Task—0
TMU Japanese-English Multimodal Machine Translation System for WAT 2020—0
Understanding the Effect of Textual Adversaries in Multimodal Machine Translation—0
Transformer-based Cascaded Multimodal Speech Translation—0
Multilingual Multimodal Machine Translation for Dravidian Languages utilizing Phonetic Transcription—0
Multimodal Machine Translation through Visuals and Speech—0
Multimodal Machine Translation with Reinforcement Learning—0
Multimodal Machine Translation with Visual Scene Graph Pruning—0
Multimodal Neural Machine Translation System for English to Bengali—0
MultiNews: A Web collection of an Aligned Multimodal and Multilingual Corpus—0
NICT-NAIST System for WMT17 Multimodal Translation Task—0
Multi30K: Multilingual English-German Image DescriptionsCode0
Video-Helpful Multimodal Machine TranslationCode0
Multimodal Lexical TranslationCode0
A Visual Attention Grounding Neural Model for Multimodal Machine TranslationCode0
Findings of the Third Shared Task on Multimodal Machine TranslationCode0
Multimodal Machine Translation with Embedding PredictionCode0
Distilling Translations with Visual AwarenessCode0
Cultural and Geographical Influences on Image Translatability of Words across LanguagesCode0
Latent Variable Model for Multi-modal TranslationCode0
Vision Matters When It Should: Sanity Checking Multimodal Machine Translation ModelsCode0
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All datasetsMulti30KHindi Visual Genome (Challenge Set)Hindi Visual Genome (Test Set)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1delMeteor (EN-FR)74.6—Unverified
2ERNIE-UniX2BLEU (EN-DE)49.3—Unverified
3IKD-MMTBLEU (EN-DE)41.28—Unverified
4DCCNBLEU (EN-DE)39.7—Unverified
5CaglayanBLEU (EN-DE)39.4—Unverified
6Gumbel-Attention MMTBLEU (EN-DE)39.2—Unverified
7Multimodal TransformerBLEU (EN-DE)38.7—Unverified
8ImagiTBLEU (EN-DE)38.4—Unverified
9del+objBLEU (EN-DE)38—Unverified
10VMMTFBLEU (EN-DE)37.6—Unverified
#ModelMetricClaimedVerifiedStatus
1ViTABLEU (EN-HI)51.6—Unverified
#ModelMetricClaimedVerifiedStatus
1ViTABLEU (EN-HI)44.6—Unverified