terrencetao/asr_ewondo

asr_ewondo This is the model for Wav2Vec2-Large-XLSR-Ewondo, a fine-tuned facebook/wav2vec2-large-xlsr-53 model on the dataset collected by the IDASCO Team ### 0. Setup Environment : torch json codecs datasets soundfile torchaudio argparse tokenizers transformers speechbrain pandas dataclasses typing tqdm numpy sentencepiece All the python packages can be installed via `pip install` ### 1. Description #### 1.2 Dataset We constructed a corpus from 103 sentences read by 5 speakers. We randomly selected 11 sentences for the test (2min30s) and 92 remaining sentences for the training (21min51s) #### 1.3 running: - Define the tokenization method: All: letter + tone , char: tone separate to letter and BPE `python3 custom_tokenizer.py --dataset train --tokenizer all` - Running asr `python3 custom_asr.py --model $model --$tok`