Welcome to the home page of the Wolof ASR Model Kaggle Hackathon! This competition focuses on building an Automatic Speech Recognition (ASR) model for Wolof, a low-resource language spoken in Senegal and West Africa. Due to limited available datasets and linguistic resources, creating an accurate ASR model for Wolof presents unique challenges.

Participants should note that there are hardware limitations for this hackathon: GPU resources on Google Colab are limited to the T4 model, and training time is capped at 5 hours per session. These constraints encourage innovative approaches to optimize model performance within these boundaries, enhancing participants' skills in resource-efficient machine learning.

Goal: The goal of this hackathon is to build effective ASR models that can overcome data scarcity and hardware constraints, advancing the field of speech recognition for low-resource languages like Wolof.