Handy is an open-source, on-device automatic speech-to-text application designed to enhance accessibility by providing free, private, and simple transcription capabilities directly on a user's computer. Its core methodology revolves around local audio processing, eliminating the need for cloud-based data transmission, thus ensuring user privacy as voice data remains on the local machine.

The system operates by capturing spoken language via a user-defined keyboard shortcut. When activated, the application initiates an audio recording session from the user's microphone. This audio stream is then fed into a locally deployed Automatic Speech Recognition (ASR) model. Unlike typical commercial ASR services that offload computational demands to remote servers, Handy processes the audio entirely on the user's machine. This on-device processing converts the raw audio waveform into text, leveraging an unspecified but locally executed ASR algorithm. Upon completion of the recording session, triggered either by the release of the shortcut key (in the default push-to-talk mode) or a second press of the key combination (in toggle mode), the transcribed text is automatically pasted into the currently active text field, simulating direct keyboard input.

Key features supporting this methodology include:

• Configurable Activation: Users can choose between a "push-to-talk" mode, where transcription occurs while a key is held down and finalizes upon release, or a "toggle" mode, where one press starts recording and another stops it, followed by transcription.
• Customizable Key Bindings: The keyboard shortcut used to activate transcription is user-definable, allowing for integration into various workflows (e.g., remapping to Ctrl-Z).
• Privacy-Centric Design: By performing all ASR computations locally, Handy ensures that sensitive voice data never leaves the user's computer, addressing significant privacy concerns associated with cloud-based speech-to-text services.
• Direct Text Injection: The system seamlessly integrates with the operating environment to directly input the transcribed text into any active text input area, enhancing user efficiency.
• Visual Feedback: A dedicated transcription icon on the operating system's interface (e.g., macOS menu bar) lights up to indicate active recording and processing.

Handy aims to be a singular, focused tool for transcription, promoting an open-source development model that encourages community contributions and extensions. It is supported by sponsors to maintain its free accessibility tooling.