Portuguese FAQ for Financial Services
This addresses data scarcity for NLP researchers in the Portuguese financial domain, but it is incremental as it applies existing augmentation techniques to a new dataset.
The study tackled the scarcity of Portuguese financial domain data by using synthetic data augmentation on a Central Bank of Brazil FAQ dataset, resulting in a publicly released dataset on Hugging Face to improve accessibility for NLP applications.
Scarcity of domain-specific data in the Portuguese financial domain has disfavored the development of Natural Language Processing (NLP) applications. To address this limitation, the present study advocates for the utilization of synthetic data generated through data augmentation techniques. The investigation focuses on the augmentation of a dataset sourced from the Central Bank of Brazil FAQ, employing techniques that vary in semantic similarity. Supervised and unsupervised tasks are conducted to evaluate the impact of augmented data on both low and high semantic similarity scenarios. Additionally, the resultant dataset will be publicly disseminated on the Hugging Face Datasets platform, thereby enhancing accessibility and fostering broader engagement within the NLP research community.