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culture. These results are consistent with existing publications remarking on the state of multicultural education in music therapy.
In an increasingly global economy, companies face challenges with implementing successful business and marketing strategies in cultures different from their own. This paper calls upon previous research to compile a per-country outline of general behaviors and expectations when doing business overseas. Using categorical definitions from Hofstede's 1984 study and those found in the Handbook of Global and Multicultural Negotiation, a table has been prepared to group similar countries based on their cultural biases.
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.