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GitHub - slipboxai/swift-scribe: Fully local, no dependency scribe. Speak into your microphone and summarize. Requires iOS 26 and MacOS 26 to use the advanced transcription model and foundational model for summaries

Jun 13, 2025 · github.com
GitHub - slipboxai/swift-scribe: Fully local, no dependency scribe. Speak into your microphone and summarize. Requires iOS 26 and MacOS 26 to use the advanced transcription model and foundational model for summaries
Swift Scribe is an AI-powered speech-to-text transcription app designed exclusively for iOS 26 and macOS 26+. It utilizes Apple's Foundation Model Framework and SpeechTranscriber to provide real-time voice transcription, intelligent content analysis, and advanced text editing capabilities, all while ensuring user privacy with on-device processing. The app is aimed at transforming spoken words into organized, searchable notes, making it suitable for various applications such as business meetings, healthcare documentation, educational lectures, legal proceedings, and media content creation.

The app requires iOS 26 Beta or newer and macOS 26 Beta or newer, along with Xcode Beta and Swift 6.2+ for development. Swift Scribe's architecture includes components for audio capture, AI processing, and rich text editing. Future development phases aim to enhance features like speaker diarization, multi-language support, and platform expansion to include iOS Shortcuts and Apple Watch integration. The project is open-source under the MIT License, with acknowledgments to Apple's WWDC 2025 sessions for their frameworks and tools.

Key takeaways

  • Swift Scribe is an AI-powered transcription app designed exclusively for iOS 26 and macOS 26, utilizing on-device AI for real-time speech-to-text conversion.
  • The app leverages Apple's latest SpeechAnalyzer and SpeechTranscriber frameworks, available only in iOS 26/macOS 26, for advanced speech recognition and content analysis.
  • Swift Scribe supports various use cases, including business, healthcare, education, legal, content creation, and accessibility, enhancing workflows with AI-driven transcription.
  • The project is structured with a focus on core application logic, audio processing, AI integration, and rich text editing, and it is licensed under the MIT License.
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