Detecting the occurrences of rags’ characteristic melodic
phrases from polyphonic audio recordings is a fundamental
task for the analysis and retrieval of Indian art music.
We propose an abstraction process and a complexity
weighting scheme which improve melodic similarity
by exploiting specific melodic characteristics in this music.
In addition, we propose a tetrachord normalization to handle
transposed phrase occurrences. The melodic abstraction
is based on the partial transcription of ...
Detecting the occurrences of rags’ characteristic melodic
phrases from polyphonic audio recordings is a fundamental
task for the analysis and retrieval of Indian art music.
We propose an abstraction process and a complexity
weighting scheme which improve melodic similarity
by exploiting specific melodic characteristics in this music.
In addition, we propose a tetrachord normalization to handle
transposed phrase occurrences. The melodic abstraction
is based on the partial transcription of the steady regions
in the melody, followed by a duration truncation step.
The proposed complexity weighting accounts for the differences
in the melodic complexities of the phrases, a crucial
aspect known to distinguish phrases in Carnatic music.
For evaluation we use over 5 hours of audio data comprising
625 annotated melodic phrases belonging to 10 different
phrase categories. Results show that the proposed melodic
abstraction and complexity weighting schemes significantly
improve the phrase detection accuracy, and that
tetrachord normalization is a successful strategy for dealing
with transposed phrase occurrences in Carnatic music.
In the future, it would be worthwhile to explore the applicability
of the proposed approach to other melody dominant
music traditions such as Flamenco, Beijing opera and
Turkish Makam music.
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