examples/research_projects/wav2vec2/run_asr.py/Orthography/create_processor
class Orthography:    def create_processor(self, model_args: ModelArguments) -> Wav2Vec2Processor:
        feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained(
            model_args.model_name_or_path, cache_dir=model_args.cache_dir
        )
        if self.vocab_file:
            tokenizer = Wav2Vec2CTCTokenizer(
                self.vocab_file,
                cache_dir=model_args.cache_dir,
                do_lower_case=self.do_lower_case,
                word_delimiter_token=self.word_delimiter_token,
            )
        else:
            tokenizer = Wav2Vec2CTCTokenizer.from_pretrained(
                model_args.model_name_or_path,
                cache_dir=model_args.cache_dir,
                do_lower_case=self.do_lower_case,
                word_delimiter_token=self.word_delimiter_token,
            )
        return Wav2Vec2Processor(feature_extractor, tokenizer)