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Gorka Hernandez Villalon, iOS developer and AI automation specialistGorka Hernandez
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Timegrapher Watch

Mechanical watch timegrapher using any microphone.

Python tool that analyzes a mechanical watch sound in real time: automatic beat-rate detection, accuracy, amplitude and beat-error measurements with configurable filters.

Problem, stack and result

Problem solved

Python tool that analyzes a mechanical watch sound in real time: automatic beat-rate detection, accuracy, amplitude and beat-error measurements with configurable filters.

Technologies used

Core stack: Python, DSP, Audio. Project technologies: Python, DSP, Audio, NumPy.

What I did

My role was Author. I worked on the technical implementation, product approach and enough documentation for the result to be explained and evolved.

Result or learning

Automatic escapement frequency detection. Configurable filters for ambient noise.

Highlights

  • Automatic escapement frequency detection.
  • Configurable filters for ambient noise.
  • Low-cost alternative to professional timegraphers.