A chord distance metric based on the Tonal Pitch Space and a key-finding method for chord annotation sequences

Music Information Retrieval (MIR) is a growing field of research concerned about recovering and generating useful information about music in general. One classic problem of MIR is key-finding, which could be described as the activity of finding the most stable tone and mode of a determined musical piece or a fragment of it. This problem, however, is usually modeled for audio as an input, sometimes MIDI, but little attention seems to be given to approaches considering musical notations and musictheory. This paper will present a method of key-finding that has chord annotations as its only input. A new metric is proposed for calculating distances between tonal pitch spaces and chords, which will be later used to create a key-finding method for chord annotations sequences. We achieve a success rate from 77.85% up to 88.75% for the whole database, depending on whether or not and how some parameters of approximation are configured. We argue that musical-theoretical approaches independent of audio could still bring progress to the MIR area and definitely could be used as complementary techniques.