whisper_android and RuntimeSpeechRecognizer

These are ecosystem siblings—both are independent implementations of OpenAI's Whisper model optimized for different platforms (Android via TensorFlow Lite and Unreal Engine via whisper.cpp), rather than tools designed to work together or replace each other.

whisper_android
64
Established
Maintenance 16/25
Adoption 10/25
Maturity 16/25
Community 22/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 20/25
Stars: 630
Forks: 106
Downloads:
Commits (30d): 2
Language: C++
License: MIT
Stars: 303
Forks: 50
Downloads:
Commits (30d): 0
Language: C++
License: MIT
No Package No Dependents
Archived Stale 6m No Package No Dependents

About whisper_android

vilassn/whisper_android

Offline Speech Recognition with OpenAI Whisper and TensorFlow Lite for Android

This project offers pre-built Android apps and code examples to add offline speech recognition capabilities to Android devices. It takes spoken audio (like a voice recording) and converts it into text, all without needing an internet connection. This is for Android developers who want to integrate powerful speech-to-text features into their mobile applications.

Android-development mobile-app-development speech-to-text offline-features AI-integration

About RuntimeSpeechRecognizer

gtreshchev/RuntimeSpeechRecognizer

Cross-platform, real-time, offline speech recognition plugin for Unreal Engine. Based on Whisper OpenAI technology, whisper.cpp.

Leverages whisper.cpp for local inference without external API calls, enabling private audio processing entirely on-device. Provides both C++ and Blueprint APIs for Unreal Engine integration, with support for multiple audio input sources and real-time streaming transcription. Includes automatic model downloading and caching, allowing developers to embed various Whisper model sizes optimized for accuracy versus performance trade-offs.

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