- List all unit tests and overall system test carried out for experimentation of the system. List any findings and design changes made from your analysis of test results and other data obtained from the experimentation.
Signal Processing: ~30 samples tested, looking for pitch accuracy and onset accuracy primarily.
ML Model:
Web backend:
- What are the most significant risks that could jeopardize the success of the project? How are these risks being managed? What contingency plans are ready?
The biggest risk to the project is still the quality of generated music. Although the quality of music generated by the pre trained model is good, It’s hard to predict how the finetuning will affect the generated music. To mitigate this risk we’re researching different techniques used when fine tuning models (such as freezing certain weights) to prevent divergence.
- Were any changes made to the existing design of the system (requirements, block diagram, system spec, etc)? Why was this change necessary, what costs does the change incur, and how will these costs be mitigated going forward?
The overall design of the system remains the same.
- Provide an updated schedule if changes have occurred.
No changes