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This repository contains excercises and supporting code for the course T-717-SPST at Reykjavik University. (Work in progress)

• Exercise 1: Digital Audio
• Exercise 2: Audio Manipulation
• Exercise 3: Domain Specific TTS
• Exercise 4: Script Design
• Exercise 5: Record Your Data (work in progress)
• Exercise 6: Festival in Docker (work in progress)
• Exercise 7: Ossian in AWS (work in progress)

All the code in this repository is written in Python 3. The recommended approach is to create a python virtual environment:

• Create the virtual environment with one of the following:
  • macOS/Linux:python3 -m venv .env orvirtualenv -p python3 ..env
  • Windows:python -m venv ./env orpy -3 -m venv .env
• Activate it withsource ./env/bin/activate if you are in the project directory. Otherwise you dosource /path/to/your/environment/bin/activate.

You can however use Python in any way you see fit and perhaps you may have all the requirements already installed system wide.

Install Python requirements withpip install -r requirements.txt. You can of course install any additional python requirements usingpip, just make sure you have your virtual environment activated when you do.

To get the best experience make sure that your VS Code workspace is using the correct Python interpreter. If you are using a virtual environment then the workspace settingpython.pythonPath has to be set to/path/to/venv/bin/python. Normally VS Code takes care of doing this for you by recognizing that there is a virtual environment in the workspace. If not:

• Make sure you have the VSC Python extension installed (search forms-python.python in the extension search)
• Press the settings cog in the bottom left inside VSC and selectsettings.
• SelectWorkspace
• search forpythonpath and edit the value to point to your python interpreter as explained above.

You can read a more detailed document about python environments in VSChere.

I would recommend forking this repository before starting your work. By doing that you could easily version control your own work throughout the course. Notes:

• This repository will ignore*.wav files, except for thedata/ directories in assignments 1-3. If you want to track your results as well, either save them in these./data directories or modify the.gitignore file.
• This repository is a work in progress so when important changes are made, followthis to update your fork according to the upstream.

Each assignment has aREADME.md which includes the assignment description and what to turn in. You should return a PDF file where each question inREADME.md that is marked with(*) is answered. Try to adhere to the numbering in theREADME.md files. For example, label the answer to the first question inthis assignment as1.1. Furthermore:

• Each assignment has atemplate.py file. This file should be included in your submission with your own code filled in as well as any other helper functions you write to generate your results.
• Some assignments have anexample.py file that shows how to use some of the functions that are given intools.py.
• In some of the assignments you are asked to generate and save waveforms to disk. In those cases, it is good to include those as well.Turn in your assignment on the Canvas page for the course.