whisper_android and MisterWhisper
These are ecosystem siblings—one provides a mobile inference implementation (TensorFlow Lite on Android) while the other provides a push-to-talk interface pattern, both consuming the same Whisper model but targeting different deployment contexts and interaction models.
About whisper_android
vilassn/whisper_android
Offline Speech Recognition with OpenAI Whisper and TensorFlow Lite for Android
Provides dual implementation paths via TensorFlow Lite Java and Native APIs, allowing developers to choose between ease of integration and optimized performance. Includes a Python conversion pipeline to transform OpenAI Whisper models into TFLite format, plus support for live streaming transcription through buffer-based audio input alongside file-based batch processing. The architecture handles multilingual models with configurable vocabulary filters and manages audio preprocessing at 16kHz mono format for inference compatibility.
About MisterWhisper
openconcerto/MisterWhisper
Push to talk voice recognition using Whisper
Supports 100+ languages with GPU acceleration via whisper.cpp, enabling fast local transcription or remote server inference. Integrates with any active application through system hotkeys (F1-F18), automatically injecting recognized text with silence detection to minimize manual control. Available as standalone executables for Windows (CPU/CUDA/Vulkan variants) or as a Java-based client for Linux/macOS that connects to a whisper.cpp server locally or over the network.
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