|
--- |
|
license: apache-2.0 |
|
task_categories: |
|
- table-question-answering |
|
- question-answering |
|
- translation |
|
- text2text-generation |
|
language: |
|
- es |
|
tags: |
|
- CelebA |
|
- Spanish |
|
- celebFaces attributes |
|
- face detection |
|
- face recognition |
|
pretty_name: Sent2vec+CelebA training corpus in Spanish |
|
size_categories: |
|
- 100M<n<1B |
|
--- |
|
|
|
## Corpus Summary |
|
|
|
This corpus has 192050 entries made up of descriptive sentences of the faces of the CelebA dataset. |
|
The preprocessing of the corpus has been to translate into Spanish the captions of the CelebA dataset with the algorithm used in [Text2FaceGAN](https://arxiv.org/pdf/1911.11378.pdf). |
|
In particular, all sentences are combined to generate a larger corpus. Additionally, a data preprocessing was applied that consists of eliminating stopwords, separation symbols and complementary elements that are not useful for training. |
|
Finally, using the Sent2vec library and the corpus, training was done to obtain an encoder model for sentences in the Spanish language. Specifically for captions from the CelebA |
|
dataset |
|
|
|
The training of Sent2vec + CelebA, using the present corpus was developed, resulting in the new model [Sent2vec-CelebA-Sp](https://huggingface.co/oeg/Sent2vec_CelebA_Sp). |
|
|
|
## Corpus Fields |
|
Each corpus entry is composed of: |
|
- Descriptive sentence of a face from the CelebA dataset applied the corresponding preprocessing. |
|
|
|
You can download the file with a _.txt_ or _.csv_ extension as appropriate. |
|
|
|
## Citation information |
|
**Citing**: If you used CelebA_Sent2vec_Sp corpus in your work, please cite the paper publish in **[Information Processing and Management](https://doi.org/10.1016/j.ipm.2024.103667)**: |
|
|
|
```bib |
|
@article{YAURILOZANO2024103667, |
|
title = {Generative Adversarial Networks for text-to-face synthesis & generation: A quantitative–qualitative analysis of Natural Language Processing encoders for Spanish}, |
|
journal = {Information Processing & Management}, |
|
volume = {61}, |
|
number = {3}, |
|
pages = {103667}, |
|
year = {2024}, |
|
issn = {0306-4573}, |
|
doi = {https://doi.org/10.1016/j.ipm.2024.103667}, |
|
url = {https://www.sciencedirect.com/science/article/pii/S030645732400027X}, |
|
author = {Eduardo Yauri-Lozano and Manuel Castillo-Cara and Luis Orozco-Barbosa and Raúl García-Castro} |
|
} |
|
``` |
|
|
|
## License |
|
|
|
This corpus is available under the **[Apache License 2.0](https://github.com/manwestc/TINTO/blob/main/LICENSE)**. |
|
|
|
## Autors |
|
- [Eduardo Yauri Lozano](https://github.com/eduar03yauri) |
|
- [Manuel Castillo-Cara](https://github.com/manwestc) |
|
- [Raúl García-Castro](https://github.com/rgcmme) |
|
|
|
[*Universidad Nacional de Ingeniería*](https://www.uni.edu.pe/), [*Ontology Engineering Group*](https://oeg.fi.upm.es/), [*Universidad Politécnica de Madrid.*](https://www.upm.es/internacional) |
|
|
|
## Contributors |
|
See the full list of contributors [here](https://github.com/eduar03yauri/DCGAN-text2face-forSpanish). |
|
|
|
<kbd><img src="https://www.uni.edu.pe/images/logos/logo_uni_2016.png" alt="Universidad Politécnica de Madrid" width="100"></kbd> |
|
<kbd><img src="https://raw.githubusercontent.com/oeg-upm/TINTO/main/assets/logo-oeg.png" alt="Ontology Engineering Group" width="100"></kbd> |
|
<kbd><img src="https://raw.githubusercontent.com/oeg-upm/TINTO/main/assets/logo-upm.png" alt="Universidad Politécnica de Madrid" width="100"></kbd> |
|
|
|
|
|
|