abdoukarim/wolbanking77

Wolof Banking Speech Intent Classification Dataset training and evaluation code. # Wolbanking77: Wolof Banking Speech Intent Classification Dataset Paper link # Abstract Intent classification models have made a significant progress in recent years. However, previous studies primarily focus on high-resource language datasets, which results in a gap for low-resource languages and for regions with high rates of illiteracy, where languages are more spoken than read or written. This is the case in Senegal, for example, where Wolof is spoken by around 90\% of the population, while the national illiteracy rate remains at of 42\%. Wolof is actually spoken by more than 10 million people in West African region. To address these limitations, we introduce the Wolof Banking Speech Intent Classification Dataset (WolBanking77), for academic research in intent classification. WolBanking77 currently contains 9,791 text sentences in the banking domain and more than 4 hours of spoken sentences. Experiments on various baselines are conducted in this work, including text and voice state-of-the-art models. The results are very promising on this current dataset. In addition, this paper presents an in-depth examination of the dataset’s contents. We report baseline F1-scores and word error rates metrics respectively on NLP and ASR models trained on WolBanking77 dataset and also comparisons between models. # Getting Started You can download a copy of the dataset (distributed under the CC-BY-4.0 license) available on Kaggle using the following link: - Wolbanking77 on Kaggle Copy the text directory to the following directory : ```dataset/``` Copy the audio directory to the following directory : ```dataset/``` # Requirements ## NLP ### Baselines To install requirements for baseline models (KNN, SVM, Logistic Regression, Naive Bayes, LASER+MLP, LASER+CNN): ```shell pip install -r tasks/nlp/ml_baselines_script/requirements_baseline.txt ``` ### BertBase To install requirements for BertBase : ```shell sh setup_bert_base.sh ``` ### AfroXLMR To install requirement …