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Modulo7 is an research attempt to build a Higher level MIR engine (Music Information Retrieval Engine) using music theory and natural language principles. Most music recommendation engines take into account user feedback for recommendation and analysis purpose. At the heart of every user's choice on which song sounds good is a solid objective music theoretic basis on which the user "likes" a particular song. For instance many pop songs have I V vi IV chord progression. Modulo7 leverages these concepts to make a bleeding edge music analyzer which structurally analyzes songs and lyrics
In the other end of the spectrum most academic MIR engines rely on low level features instead of higher level music theory constructs. By doing this, the recognizers miss out of novel ideas of how melodies interact with each other and why certain songs are similar to one another structurally.
The target audience are musicologists who wish to analyze songs of different sources quickly and efficiently while screening out songs based on what music theoretic criteria they satisfy.
Modulo7 is still in active development and not ready for consumption.