Discuss the capabilities and limitations of folk-rnn models

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Reference no: EM133792044

Question 1

What are the key terms and concepts in the article? What is the general field of research?

What is the problem that the article is trying to solve? Also, what are the major contributions of the paper?

Question 2

2.1 What is the main aim of applying machine learning to music data?

2.2 What work has been done before in this field and how can you describe the existing research in terms of momentum and direction?

Question 3

There are three major ways that authors present an argument:
Reasoning, in which the author presents a logical explanation of the argument.
Evidence, in which the author presents statistics, facts, and studies to prove his point.
Appeal, in which the author appeals to the reader's emotions to elicit empathy.

Required:
3.1 How has the author of the article structured the arguments?

3.2 How authoritative and credible is the evidence?

Question 4

4.1 Discuss the advantages of DeepBach, which is an LSTM-based statistical model aimed at modelling chorale music.

4.2 Discuss the capabilities and limitations of folk-rnn models.

Question 5

5.1 Are there any open questions in the article that require further study?

5.2 Provide some recommendations for future research.

Reference no: EM133792044

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