CS 224D Final Project DeepRock
نویسندگان
چکیده
We create a canonical encoding for multi-instrument MIDI songs into natural language, then use deep NLP techniques such as character LSTM variants to compose rock music that surpasses the prior state of the art and is competitive with certain pieces of music composed by human rock bands. We further define a neural network architecture for learning multi-instrument music generation in concert, but due to space and time constraints are unable to sufficiently train it.
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Keyphrases: Intrinsic and extrinsic evaluations. Effect of hyperparameters on analogy evaluation tasks. Correlation of human judgment with word vector distances. Dealing with ambiguity in word using contexts. Window classification. This set of notes extends our discussion of word vectors (interchangeably called word embeddings) by seeing how they can be evaluated intrinsically and extrinsically...
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تاریخ انتشار 2016