Arabic speech recognition, classification and text-to-speech.
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Updated
Sep 30, 2023 - Jupyter Notebook
Arabic speech recognition, classification and text-to-speech.
The official submission from Speech Squad team for the MTC-AIC 2 competition of 2024 where an ASR model is developed tailored for the Egyptian dialect, utilizing the FastConformer architecture. Our four-stage training pipeline achieved a Mean Levenshtein Distance score of 9.58 on the test set.
This project implements an Arabic Speech Recognition system using an ensemble voting classifier. The model is built with Python and utilizes the Librosa library for preprocessing and feature extraction.
Fine-tuning Multilingual Large Speech Recognition Models: Wav2vec and Whisper
This project implements an Arabic Speech Recognition system using an ensemble voting classifier. The model is built with Python and utilizes the Librosa library for preprocessing and feature extraction.
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