BetterWispr

OpenWhispr is an open-source, cross-platform desktop voice-to-text application for macOS, Windows, and Linux. A global hotkey captures speech and inserts the resulting text at the cursor in another application; dictation can use local Whisper or NVIDIA Parakeet speech-to-text engines, where audio remains on the device, or cloud providers through user-supplied keys. It also supports dictation translation, AI-agent commands, meeting transcription with speaker diarization and voice fingerprinting, audio and video transcription, and searchable notes with semantic search and optional cloud sync. The application is built with Electron, React, TypeScript, SQLite, whisper.cpp, and sherpa-onnx, and provides an API and MCP server for programmatic access to notes and transcriptions. The repository describes it as having no data collection or telemetry and distributes installers for the three supported desktop platforms. It is licensed under the MIT license.

BetterVoice is an experimental, open-source macOS menu-bar app for local voice dictation with screen context. It transcribes speech locally and captures the full display whenever the user circles an area with the pointer, marking each capture with a blue pointer trail and pulse while preserving multiple references in order. The app inserts the transcript into the selected text field when macOS permits it and pastes captured images when both speech and screen context are available. It supports quick notes and long explanations, configurable microphones, dictation languages, circle-detection thresholds, and keyboard shortcuts. English uses a local Parakeet model by default, while other languages use a separately downloaded multilingual model; an optional English-only grammar-cleanup feature runs locally through quantized ONNX weights.

Lipflow is an open-source, cross-platform silent lip-reading dictation tool that uses a webcam to turn mouthed words into text pasted at the cursor. It runs locally on macOS, Windows, and Linux: face landmarks are tracked live, 96×96 grayscale mouth crops are sampled at 25 fps, and an Auto-AVSR visual-speech-recognition pipeline combines a 3D-convolutional ResNet front end, Conformer encoder, Transformer decoder, CTC scoring, and a subword language model with beam search. Users can train the language model and lip reader on their phrasing and face, import local Wispr Flow dictation history, and optionally apply cleanup through offline rules, an on-device Qwen model, Claude, Codex CLI, or Ollama. Whisper mode combines lip and audio input with an audio-visual model while the hotkey is held. The repository is MIT-licensed, although its LRS3-trained model weights are identified as for non-commercial research use.