Note & Scalar Recognition is crucial because music comprises a blending of instruments emanating sounds made at a number of different frequencies.  The manner in which these frequencies blend is important to the making and enjoyment of music. Mathematical rules attributed to musical scales define the blend and hence genre or mood of the score.

Knowing the scale of a score is necessary for music analysis such as mood induction because the mode of the key is deemed to provide a specific emotional connotation. The pitch distance of musical notes based on chromatic scale determines human’s perception of music.

The problem is not as trivial as measuring intervals and we present an approach using classification rules and action rules to understand and interact with scalar music theory. Following is an example of this goal.

Our proposed Online Music Information Retrieval system comprises a methodology wherein a user can retrieve music from the internet through non-semantic instructions and then manipulate the songs to sound the way the user would like them to sound.

First the user instructs the online search engine, through Audio input, for a certain number of songs that "sound something like ..." Upon the Audio recognition system confirms with the user that it interpreted the songs correctly. Upon confirmation the search engine will use UNCC's MIRAI Automated Music Indexing System to retrieve the requested amount of songs.

On the last step the user is able to manipulate and contort the manner in which he hears the songs.

Music Dissemination under contsruction

Search by humming under contsruction