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Bronze Age sites on Cyprus have produced the largest dataset of game boards belonging to any ancient culture. Weight and morphological data were gathered from these artifacts to determine the likelihood of their portability and to identify what type of game was present. The presence of fixed and likely immobile games, as well as the presence of clusters of portable games, was used to identify spaces in which games were played. Counts of other types of artifacts found in the same spaces as games were tabulated, and Correspondence Analysis (CA) was performed in order to determine differences in the types of activities present in the same spaces as play.
The results of the CA showed that during the Prehistoric Bronze Age, which has fewer indicators of social complexity, gaming spaces were associated with artifacts related to consumption or specialty, heirloom and imported ceramics, and rarely played in public spaces. During the Protohistoric Bronze Age, when Cyprus was more socially complex, games were more commonly played in public spaces and associated with
artifacts related to consumption. These changes suggest a changing emphasis through time, where the initiation and strengthening of social bonds through the grounding process afforded by play is more highly valued in small-scale society, whereas the social mobility that is enabled by performance during play is exploited more commonly during periods of complexity.
The purpose of this project is to create a useful tool for musicians that utilizes the harmonic content of their playing to recommend new, relevant chords to play. This is done by training various Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs) on the lead sheets of 100 different jazz standards. A total of 200 unique datasets were produced and tested, resulting in the prediction of nearly 51 million chords. A note-prediction accuracy of 82.1% and a chord-prediction accuracy of 34.5% were achieved across all datasets. Methods of data representation that were rooted in valid music theory frameworks were found to increase the efficacy of harmonic prediction by up to 6%. Optimal LSTM input sizes were also determined for each method of data representation.
My proposed project is an educational application that will seek to simplify the<br/>process of internalizing the chord symbols most commonly seen by those learning<br/>musical improvisation. The application will operate like a game, encouraging the<br/>user to identify chord tones within time limits and award points for successfully<br/>doing so.