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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def dense_to_human_readable(dense_repr: Sequence[Sequence[int]], index_to_label: Dict[int, str]) -> List[List[str]]: """ Converts a dense representation of model decoded output into human readable, using a mapping from indices to labels. """


    transcripts = []
    for dense_r in dense_repr:
        non_empty_phonemes = [phn_i for phn_i in dense_r if phn_i != 0]
        transcript = [index_to_label[index] for index in non_empty_phonemes]
        transcripts.append(transcript)

    return transcripts