{'fraction_non_alphanumeric': 0.0070921985815602835, 'fraction_numerical': 0.0, 'mean_word_length': 5.247787610619469, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
The Study of Melodic Similarity using Manual Annotation and Melody Feature Sets

This paper describes both a newly developed method for manual annotation for aspects of melodic similarity and its use for evaluating melody features concerning their contribution to perceived similarity. The second issue is also addressed with a computational evaluation method. These approaches are applied to a corpus of folk song melodies. We show that classification of melodies could not be based on single features and that the feature sets from the literature are not sufficient to classify melodies into groups of related melodies. The manual annotations enable us to evaluate various models for melodic similarity.