Audio Data Insights

Example Jupyter Notebooks and sample data put together for learning and presentation.

Digital Audio data contains sounds that have been recorded and converted into digital form. One example is conversation and user interactions with voice applications. The code in this repo explores different types of features that you can use when working to extract features and information from audio data. Further, we These sample notebooks were built to use for demos and learning how to work with audio data.

The related presentation slide deck can be found here.

Shared Data

For ease of setup, you can download the data needed to run the notebooks in this repo here. Once downloaded, just unzip the compressed file and place the contents in a folder named data inside of your working directory.

Running the Notebooks

1. Fork and Pull this Repo

2. Change Directory into your local version of this Repo.

3. Install Python 3.6 or later.

4. Create a Virtual Environment: python3 -m venv <path-to-venvs\env_name>

5. Actiivate the Virtual Environment: source <path-to-venvs\env_name>\bin\activate

6. Install Jupyter Lab: pip install jupyterlab

7. Install Project Requirements: pip install -r requirements.txt

8. Start Jupyter Lab jupyter lab

Meta

Ryan Bales – @ryanbales – ryan@balesofdata.com

Distributed under the Apache 2.0 license. See LICENSE for more information.

https://github.com/ryanbales/

Contributing

1. Fork it (https://github.com/ryanbales/Audio-Data-Insights/fork)
2. Create your feature branch (git checkout -b feature/fooBar)
3. Commit your changes (git commit -m "<comments>")
4. Push to the branch (git push origin feature/fooBar)
5. Create a new Pull Request