A model of inter-musician communication for Artificial Musical Intelligence

Artificial Musical Intelligence is a subject that spans a broad array of disciplines related to human cognition, social interaction, cultural understanding, and music generation. Although significant progress has been made on particular areas within this subject, the combination of these areas remains largely unexplored. In this dissertation, we propose an architecture that facilitates the integration of prior work on Artificial Intelligence and music, with a focus on enabling computational creativity. Specifically, our architecture represents the verbal and non-verbal communication used by human musicians using a novel multi-agent interaction model, inspired by the interactions that a jazz quartet exhibits when it performs. In addition to supporting direct communication between autonomous musicians, our architecture presents a useful step toward integrating the different subareas of Artificial Musical Intelligence.Tónlistargervigreind er grein sem spannar fjölbreytt svið tengd mannlegri þekkingu, félagslegum samskiptum, skilningi á menningu og gerð tónlistar. Þrátt fyrir umtalsverða framþróun innan greinarinnar, hefur samsetning einstakra sviða hennar lítið verið rannsökuð. Í þessari ritgerð eru lögð drög að leið sem stuðlar að samþættingu eldri verka á sviði gervigreindar og tónlistar, með áherslu á getu tölva til sköpunar. Nánar tiltekið lýtur ritgerðin að samskiptum sem notuð eru af tónlistarmönnum við nýju samskiptalíkani fyrir fjölþætt samskipti, sem er innblásið af samskiptum jazz kvarteta á sviði. Til viðbótar við stuðning við bein samskipti sjálfvirkra "tónlistarmanna, felst í rannsókninni framþróun samþættingar ólíkra undirsviða tónlistargervigreindar

TwitSong: A current events computer poet and the thorny problem of assessment.

This thesis is driven by the question of how computers can generate poetry, and how that poetry can be evaluated. We survey existing work on computer-generated poetry and interdisciplinary work on how to evaluate this type of computer-generated creative product. We perform experiments illuminating issues in evaluation which are specific to poetry. Finally, we produce and evaluate three versions of our own generative poetry system, TwitSong, which generates poetry based on the news, evaluates the desired qualities of the lines that it chooses, and, in its final form, can make targeted and goal-directed edits to its own work. While TwitSong does not turn out to produce poetry comparable to that of a human, it represents an advancement on the state of the art in its genre of computer-generated poetry, particularly in its ability to edit for qualities like topicality and emotion