Fine-Tune XLSR-Wav2Vec2 for low-resource ASR with 🤗 Transformers

1. 1Prepare data, tokenizer, and feature extractor for XLSR-Wav2Vec2
2. 2Create Wav2Vec2CTCTokenizer and Wav2Vec2FeatureExtractor
3. 3Preprocess data for training
4. 4Set up a trainer for fine-tuning XLSR-Wav2Vec2
5. 5Train and evaluate the model

ML engineers and researchers can benefit from this tutorial to improve ASR models for low-resource languages, and data scientists can apply these techniques to similar NLP tasks

💡 Fine-tuning XLSR-Wav2Vec2 can improve ASR performance for low-resource languages

🗣️ Fine-tune XLSR-Wav2Vec2 for low-resource ASR with Hugging Face Transformers! 🚀