src/transformers/models/speech_to_text/feature_extraction_speech_to_text.py/Speech2TextFeatureExtractor/normalize
class Speech2TextFeatureExtractor:    def normalize(
        self, input_features: List[np.ndarray], attention_mask: Optional[np.ndarray] = None
    ) -> List[np.ndarray]:
        lengths = attention_mask.sum(-1) if attention_mask is not None else [x.shape[0] for x in input_features]
        return [
            self.utterance_cmvn(x, n, self.normalize_means, self.normalize_vars, self.padding_value)
            for x, n in zip(input_features, lengths)
        ]