Microcontroller student projects

Cornell University, , Prof. Bruce Land

Updated On 02 Feb, 19



Lecture 18: Auto-composing keyboard synth

4.1 ( 11 )

Lecture Details

Generally, our composing algorithm takes in three inputs and consists of three stages of composing. The first input that user has to enter is the mood of music that heshe wishes to create. Currently, we support two moods happy and tender. The other two inputs are two notes chosen by the user. In the first stage of composing, the tone of the music is determined as a result of the three inputs. Happy mood corresponds to a major tone determined by the two input notes, while tender mood corresponds to a minor tone determined by the two input notes. The speed of the music is also determined in the first stage by the mood input. The next stage is to create the melody for the music. The first step is to set rhythm corresponding to different moods. After the rhythm is set, the next note of the melody is chosen roughly according to the corresponding Markov probability matrix until all notes of the melody is filled. We incorporate composing rules that cannot be represented by the probability matrix to the melody composing process by either setting certain notes deterministically or changing the probability matrix when choosing notes for some special rhythm. After the melody is set, our algorithm chooses proper chord for it. The chord is chosen so that it sounds harmonic together with the melody and also varies with some randomness to avoid monotony. There is a special train mode in our composing system that lets the user to build his or her own Markov probability matrix instead of using our pre-trained ones. If the user chooses to enter the train mode, the system allows the user to play a piece of music on the electric piano. Then the system will compute the Markov probability matrix based on the piece of music that the user played and thus could generate music that assemblies what the user just played with some variations.



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Excellent course helped me understand topic that i couldn't while attendinfg my college.

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Great course. Thank you very much.