This repository is for planning, designing, and configuring macropads optimized for speech-to-text dictation workflows. Speech recognition has replaced traditional typing as the primary text input method, requiring dedicated hardware controls for seamless voice recording and transcription operations.
This is a comprehensive planning and development project covering:
- Configuration Planning: Key layout design and mapping strategies for existing hardware
- Custom Hardware Design: Physical layout design for purpose-built dictation controllers
- Bill of Materials (BOM): Component planning for custom builds
- Custom Keycaps: Design and sourcing of labeled keycaps for specific dictation functions
- 3D Printing: Case and enclosure design for custom macropads
- Ergonomic Optimization: Hand positioning and button placement for all-day use
While USB foot pedals and single-button devices exist, there's a gap for specialized multi-button controllers designed specifically for dictation workflows. This project aims to fill that gap with custom solutions tailored for intensive speech-to-text usage.
The macropads control these essential dictation operations:
- Start/stop recording
- Stop and transcribe (combined operation)
- Send for transcription
- Append to existing recording
- Delete recording
- Format selection (notes, blog ideas, etc.)
- Document existing hardware inventory
- Design optimal key layouts for each device type
- Create configuration profiles for current macropads
- Design custom hardware solutions
- Develop BOMs and 3D printable designs
- Build and test prototypes
- Refine based on real-world usage
- OS: Ubuntu 25.10 (KDE Plasma on Wayland)
- Key Remapping: Input Remapper
- Firmware: QMK for compatible devices
- Integration: Custom voice notepad interface
/macropads/- Existing hardware documentation/configurations/- Key mapping configurations/designs/- Custom hardware designs and CAD files/bom/- Bills of materials for custom builds/keycaps/- Custom keycap designs and specifications
Note: This is a personal project focused on creating optimal tools for speech-to-text workflows, not a commercial endeavor.