task_categories:translation task_categories:image-to-text task_categories:text-to-image size_categories:10K<n<100K language:ha license:cc-by-nc-sa-4.0 region:us
Multi-modal Machine Translation (MMT) enables the use of visual information to enhance the quality of translations, especially where the full context is not available to enable the unambiguous translation in standard machine translation. Despite the increasing popularity of such technique, it lacks sufficient and qualitative datasets to maximize the full extent of its potential. Hausa, a Chadic language, is a member of the Afro-Asiatic language family. It is estimated that about 100 to 150 million people speak the language, with more than 80 million indigenous speakers. This is more than any of the other Chadic languages. Despite the large number of speakers, the Hausa language is considered as a low resource language in natural language processing (NLP). This is due to the absence of enough resources to implement most of the tasks in NLP. While some datasets exist, they are either scarce, machine-generated or in the religious domain. Therefore, there is the need to create training and evaluation data for implementing machine learning tasks and bridging the research gap in the language. This work presents the Hausa Visual Genome (HaVG), a dataset that contains the description of an image or a section within the image in Hausa and its equivalent in English. The dataset was prepared by automatically translating the English description of the images in the Hindi Visual Genome (HVG). The synthetic Hausa data was then carefully postedited, taking into cognizance the respective images. The data is made of 32,923 images and their descriptions that are divided into training, development, test, and challenge test set. The Hausa Visual Genome is the first dataset of its kind and can be used for Hausa-English machine translation, multi-modal research, image description, among various other natural language processing and generation tasks.
@inproceedings{abdulmumin-etal-2022-hausa,
    title = "{H}ausa Visual Genome: A Dataset for Multi-Modal {E}nglish to {H}ausa Machine Translation",
    author = "Abdulmumin, Idris and Dash, Satya Ranjan and Dawud, Musa Abdullahi and Parida, Shantipriya and Muhammad, Shamsuddeen and Ahmad, Ibrahim Sa{'}id and Panda, Subhadarshi and Bojar, Ond{\v{r}}ej and Galadanci, Bashir Shehu and Bello, Bello Shehu",
    booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2022.lrec-1.694",
    pages = "6471--6479"
}
---
license: cc-by-nc-sa-4.0
task_categories:
- translation
- image-to-text
- text-to-image
language:
- ha
pretty_name: HaVG
size_categories:
- 10K<n<100K
dataset_info:
  features:
  - name: image
    dtype: image
  - name: X
    dtype: int16
  - name: Y
    dtype: int16
  - name: Width
    dtype: int16
  - name: Height
    dtype: int16
  - name: en_text
    dtype: string
  - name: ha_text
    dtype: string
  splits:
  - name: train
    num_bytes: 7540844
    num_examples: 28930
  - name: validation
    num_bytes: 258165
    num_examples: 998
  - name: test
    num_bytes: 413850
    num_examples: 1595
  - name: challenge_test
    num_bytes: 403770
    num_examples: 1400
  download_size: 4644869592
  dataset_size: 8616629
---
# HaVG: Hausa Visual Genome

## Dataset Description

- **Homepage:** 
- **Repository:** 
- **Paper:** 
- **Leaderboard:** 
- **Point of Contact:** 

### Dataset Summary

The Hausa Visual Genome (HaVG) dataset contains the description of an image or a section within the image in Hausa and its equivalent in English. The dataset was prepared by automatically translating the English description of the images in the Hindi Visual Genome (HVG). The synthetic Hausa data was then carefully post-edited, taking into cognizance the respective images. The data is made of 32,923 images and their descriptions that are divided into training, development, test, and challenge test set. The Hausa Visual Genome is the first dataset of its kind and can be used for Hausa-English machine translation, multi-modal research, image description, among various other natural language processing and generation tasks.

### Supported Tasks

- Translation
- Image-to-Text
- Text-to-Image

### Languages

- Hausa
- English

## Dataset Structure

### Data Fields

All the text files have seven columns as follows:

- Column1 - image_id
- Column2 - X
- Column3 - Y
- Column4 - Width
- Column5 - Height
- Column6 - English Text
- Column7 - Hausa Text

### Data Splits

| Dataset | Segments | English Words | Hausa Words |
| -------- | ----- | ----- | ----- |
| Train | 28,930 | 143,106 | 140,981 |
| Dev | 998 | 4922 | 4857 |
| Test | 1595 | 7853 | 7736 |
| Challenge Test | 1400 | 8186 | 8752 |
| Total | 32,923 | 164067 | 162326 |

The word counts are approximate, prior to tokenization.

## Dataset Creation

### Source Data

The source data was obtained from the Hindi Visual Genome dataset, a subset of the Visual Genome data.

### Annotation process

The translations were obtained using a web application that was developed specifically for this task.

### Who are the annotators?

The dataset was created by professional translators at HausaNLP and Bayero University Kano.

### Personal and Sensitive Information

The dataset do not contain any personal or sensitive information.

## Considerations for Using the Data

### Social Impact of Dataset

HaVG will enable the creation of more qualitative models for natural language applications in Hausa language.

## Additional Information

### Licensing Information

This dataset is shared under the Creative Commons [BY-NC-SA](https://creativecommons.org/licenses/by-nc-sa/4.0/) license.

### Citation Information

If you use this dataset in your work, please cite us.

```
@inproceedings{abdulmumin-etal-2022-hausa,
    title = "{H}ausa Visual Genome: A Dataset for Multi-Modal {E}nglish to {H}ausa Machine Translation",
    author = "Abdulmumin, Idris and Dash, Satya Ranjan and Dawud, Musa Abdullahi and Parida, Shantipriya and Muhammad, Shamsuddeen and Ahmad, Ibrahim Sa{'}id and Panda, Subhadarshi and Bojar, Ond{\v{r}}ej and Galadanci, Bashir Shehu and Bello, Bello Shehu",
    booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2022.lrec-1.694",
    pages = "6471--6479"
}
```

### Contributions

[More Information Needed]