Hi,
I have different audio time-series with timestamp-based annotations of multiple start + end segment boundaries that are denoting consecutive respiration cycles.
Does anyone has an idea on how I could use supervized-learning approaches to automatically segment respiration cycles from audio time series ?
Cheerz
You can try this tool. With the adaptive windowing segmentation. https://sensiml.com/documentation/data-capture-lab/automated-labeling-tools.html. PM me if you want some help getting it set up.