Title: Machine Learning with realistic audio data using pandas and sci-kit learn.
Description: In this workshop, we will learn how to identify a speaker's gender from realistic audio data using pandas and sci-kit learn. We will go through a brief description of VOiCES data, how to view and manipulate data in Pandas, and how to train a simple model in sci-kit learn.
Requirements:
- Jupyter notebook
- Pandas
- numpy
- matplotlib
- seaborn
- librosa
- sklearn
If you haven't yet, please install Anaconda on your machine.
Prerequisites for participation (Steps A to D): A. Install Python & Jupyter Notebook if you don’t already have them: Let's set up our Python environment via Anaconda. We'll be running through the instructions for Mac OS, but the instructions for Windows and Linux systems should be very similar. Simply follow the same installation steps as described below, and follow Anaconda's recommended installation procedures. Mac OS specific installation and setup: https://docs.anaconda.com/anaconda/install/mac-os Windows specific installation and setup: https://docs.anaconda.com/anaconda/install/windows Linux specific installation and setup: https://docs.anaconda.com/anaconda/install/linux Mac OS setup Step 1: Go to the Anaconda download page and download the appropriate installer. We recommend installing the Python 3 version. Installation requires about 600M of space. If you're tight on space, you can try miniconda. Step 2: Follow Anaconda's recommended installation instructions, making note of the directory where Anaconda lives (you should be prompted to specify this, your home directory is a good choice).
B. In Terminal, install required packages: pip install pandas numpy matplotlib seaborn librosa sklearn
C. Clone the workshop repo: cd {your gitrepos folder} git clone https://github.com/ninalopatina/VOiCES_workshop
D. Run the notebook: jupyter notebook