Deep learning is spreading not only to images but also to one-dimensional signals such as audio. It can flexibly handle complex problems in various environments that were difficult with conventional signal analysis.
In this file, you can try a simple deep learning for audio data using “Hammering Test” as an example in a few minutes.
This demo introduces a workflow from "acquisition of audio data" to "network designing and learning” .
#Demo Video (in Japanese)
[8:24~] : the result of this script
Kazuya Machida (2023). Deep Learning for Hammering Test (https://github.com/k-machida/deeplearning-hammering-en/releases/tag/v1.1), GitHub. Recuperado .
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See release notes for this release on GitHub: https://github.com/k-machida/deeplearning-hammering-en/releases/tag/v1.1