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.

whisper_android
64
Established
MisterWhisper
38
Emerging
Maintenance 16/25
Adoption 10/25
Maturity 16/25
Community 22/25
Maintenance 6/25
Adoption 9/25
Maturity 16/25
Community 7/25
Stars: 630
Forks: 106
Downloads:
Commits (30d): 2
Language: C++
License: MIT
Stars: 112
Forks: 5
Downloads:
Commits (30d): 0
Language: Java
License: MIT
No Package No Dependents
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 MisterWhisper

openconcerto/MisterWhisper

Push to talk voice recognition using Whisper

This application helps you convert your spoken words into written text in real-time. You speak into your microphone, and the transcribed text instantly appears wherever your cursor is, like typing it directly. This is ideal for anyone who regularly types notes, emails, or documents and wants to use their voice for faster input across various applications.

dictation productivity speech-to-text voice-input note-taking

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