Related Issue

• Issue Music Generation Analysis #472

• LGM-SOC'21 Participant

• DevIncept Participant

• Contributor

Closes: #472

Describe the add-ons or changes you've made

Give a clear description of what have you added or modifications made
This project proposes the use of 2 models, Wavenet and LSTM to generate automatic music. WaveNet takes the chunk of a raw audio wave as an input. Raw audio wave refers to the representation of a wave in the time series domain. Given the sequence of the amplitude values, WaveNet tries to predict the successive amplitude value. Another approach for automatic music generation is based on the Long Short Term Memory (LSTM) model. The preparation of input and output sequences is similar to WaveNet. At each timestep, an amplitude value is fed into the Long Short Term Memory cell – it then computes the hidden vector and passes it on to the next timesteps.
Dataset: https://www.kaggle.com/anubhavjin/midi-data-containing-melodies

Type of change

What sort of change have you made:

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Code style update (formatting, local variables)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

How Has This Been Tested?

Describe how it has been tested
Describe how have you verified the changes made

Checklist:

• My code follows the guidelines of this project.
• I have performed a self-review of my own code.
• I have commented my code, particularly wherever it was hard to understand.
• I have made corresponding changes to the documentation.
• My changes generate no new warnings.
• I have added things that prove my fix is effective or that my feature works.
• Any dependent changes have been merged and published in downstream modules.

Screenshots (Only for Front End and UI/UX Designers)