Use case: Organize, filter and create metadata for large amounts of audio data
This example is based on the Treble10 dataset, which is freely available in the SDK. On the dataset we create metadata for all receiver positions with spatial information such as distance to walls, source-receiver distance and line of sight between sources and receivers. Furthermore metadata related to acoustic parameters such as t20, c50 and edt are also added to each individual IR. The tutorial also shows how Gaussian and uniform distributions can easily be created based on the available metadata.
The following documentation is presented as Python code running inside a Jupyter Notebook. To run it yourself you can copy/type each individual cell or directly download the full notebook, including all required files.