Malayalam Visual Genome (MVG) is a multimodal dataset consisting of text and images suitable for English-to-Malayalam multimodal machine translation task and multimodal research. We have selected short English segments (captions) from Visual Genome along with associated images and automatically translated them to Malayalam with manual post-editing, taking the associated images into account.
The training set contains 29K segments. Further 1K and 1.6K segments are provided in a development and test sets, respectively. Additionally, a challenge test set of 1400 segments was prepared for the multi-modal task. This challenge test set was created by searching for (particularly) ambiguous English words based on the embedding similarity and manually selecting those where the image helps to resolve the ambiguity.
Will be updated soon.
If you use this corpus, please cite the following paper:
@article{parida2019hindi, title={Hindi Visual Genome: A Dataset for Multi-Modal English to Hindi Machine Translation}, author={Parida, Shantipriya and Bojar, Ond{\v{r}}ej and Dash, Satya Ranjan}, journal={Computaci{\'o}n y Sistemas}, volume={23}, number={4}, year={2019} }