src/transformers/pipelines/automatic_speech_recognition.py/AutomaticSpeechRecognitionPipeline/postprocess
class AutomaticSpeechRecognitionPipeline:    def postprocess(self, model_outputs):
        skip_special_tokens = False if "CTC" in self.tokenizer.__class__.__name__ else True
        recognized_string = self.tokenizer.decode(model_outputs, skip_special_tokens=skip_special_tokens)
        return {"text": recognized_string}