Comparing Spectrogram Front-Ends for Abnormal Heart-Sound Detection with a Convolutional Neural Network
Heart disease kills a lot of people, and one cheap way to catch it early is by listening to heart sounds with a stethoscope, or better yet, just recording them and running them through a model. This project is a binary classification task: take a short clip of someones heartbeat and decide if it sounds normal or abnormal. Instead of trying out a bunch of different models, we kept the CNN the same the whole time and just changed how we turned the raw audio into a picture for it to look at. We tried three ways of doing that: a regular logmel spectrogram, PCEN (which basically normalizes each frequency bin over time), and a multi resolution version that stacks a few different window sizes to...
| Authors | Abhinav Pala, Dhanush Pala |
|---|---|
| Primary category | cs.CY |
| Published | 12 June 2026 |
| Last updated at source | 12 June 2026 |
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