This repository hosts an Automatic Speech Recognition (ASR) model for the Wolof language, fine-tuned from Wav2Vce2.0 model. This model aims to provide accurate transcription of Wolof audio data.
The dataset used for training and evaluating this model is a collection from various sources, ensuring a rich and diverse set of Wolof audio samples. The collection is available in my Hugging Face account is used by keeping only the audios with duration shorter than 6 second.
For detailed information about the dataset, please refer to the
M9and2M/Wolof_ASR_dataset.
The training process was adapted from the code in the
Finetune Wa2vec 2.0 For Speech Recognition written to fine-tune Wav2Vec2.0 for speech recognition. Special thanks to the author, Duy Khanh, Le for providing a robust and flexible training framework.
This model was built using Facebook's
Wav2Vec2.0 architecture and fine-tuned with a dataset collected from various sources. Special thanks to the creators and contributors of the dataset.
This model has been developed in the context of my Master Thesis at ETSIT-UPM, Madrid under the supervision of Prof. Luis A. Hernández Gómez.
For any inquiries or questions, please contact
mamadou.marone@ensea.fr
