whisper_android and whisper.unity
These are ecosystem siblings—both are platform-specific implementations of the same underlying Whisper model (one using TensorFlow Lite for Android, the other using whisper.cpp for Unity3D), enabling offline speech recognition across different development environments rather than competing with each other.
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 whisper.unity
Macoron/whisper.unity
Running speech to text model (whisper.cpp) in Unity3d on your local machine.
Provides C++ bindings to whisper.cpp with support for 60+ languages, cross-language translation, and optional GPU acceleration via Vulkan (Windows/Linux) or Metal (Apple platforms). Includes swappable model weights ranging from tiny (fastest) to large (highest accuracy), all running inference locally without internet. Distributes as a Unity Package with prebuild libraries for Windows, macOS, Linux, iOS, Android, and visionOS.
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