Automatic scoring of singing voice based on melodic similarity measures

A method for automatic assessment of singing voice is proposed. Such method quantifies in a meaningful way the similarity between the user performance and a reference melody. A set of melodic similarity measures comprising intonation and rhythmic aspects have been implemented for this goal. Such measure implement different MIR techniques, such as melodic transcription or score alignment. The reference melody is a professional performance of the melody, but the original score could be also used with minor changes in the schema. In a first approach, only intonation, rhythm and overall score have been considered. A polynomial combination of the similarity measures output are finally used to compute the final score. The optimal combination has been obtained by data fitting from a set of scores given by real musicians to different melodies. The teacher criteria is specially well modelled for pitch intonation evaluation. The general schema is also applicable to more complex aspects such as dynamics or expressiveness if some other meaningful similarity measures are included. Computing Reviews (1998)