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TTSKit Example App

Examples/TTS/TTSKitExample/README.md

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TTSKit Example App

TTSKitExample is the demo app for TTSKit, an on-device text-to-speech framework powered by Core ML. It runs on macOS and iOS with no server required.

Requirements

  • macOS 15.2 or later.
  • iOS 18.2 or later.
  • Xcode 16.3 or later.

Building & Running

  1. Open Examples/TTS/TTSKitExample/TTSKitExample.xcodeproj in Xcode.
  2. Select the TTSKitExample scheme and your target device.
  3. Set up signing: In the project navigator, select the TTSKitExample target. Go to the Signing & Capabilities tab, then:
    • Choose your Apple Developer Team from the Team dropdown.
    • Make sure a unique bundle identifier is set.
    • Xcode will automatically handle provisioning; resolve any signing issues if prompted.
  4. Build and run (Cmd+R). Dependencies resolve automatically via SPM.

On first launch, the app prompts you to download a model. Downloads are cached in your Documents directory and reused across launches.

Private HuggingFace Repos

If you use a private model fork, set a token in ViewModel.swift:

swift
let config = TTSKitConfig(model: selectedPreset, modelToken: "hf_...")

Features

  • Model management. Download, prewarm, load, and unload models from the sidebar.
  • Two model sizes. 0.6B (fast, all platforms) and 1.7B (higher quality, style instructions, macOS only).
  • Real-time streaming. Audio starts playing before generation completes.
  • Adaptive buffering. The .auto strategy measures first-step speed and pre-buffers accordingly.
  • 9 voices. Ryan, Aiden, Ono Anna, Sohee, Eric, Dylan, Serena, Vivian, Uncle Fu.
  • 10 languages. English, Chinese, Japanese, Korean, German, French, Russian, Portuguese, Spanish, Italian.
  • Style instructions. Natural-language prosody control (1.7B only).
  • Generation history. All outputs saved as M4A with embedded metadata, reconstructed at launch.
  • Favorites. Star generations to pin them at the top of the sidebar.
  • Waveform. Live visualization that updates during streaming.
  • Settings. Temperature, top-K, repetition penalty, max tokens, chunking, compute units.
  • Copy audio. One-tap copy of the M4A to clipboard.

Project Structure

TTSKitExample/
├── TTSKitExampleApp.swift        entry point
├── ContentView.swift             root NavigationSplitView
├── SidebarView.swift             model management + history
├── DetailView.swift              input form, waveform, playback
├── ModelManagementView.swift     download / load / unload
├── GenerationSettingsView.swift  advanced options sheet
├── ViewModel.swift               @Observable view model
├── AudioMetadata.swift           Codable metadata embedded in .m4a files
├── WaveformView.swift            live waveform bar chart
└── ComputeUnitsView.swift        per-component compute unit picker

Persistence is file-based. Each generation is a self-contained .m4a file with all metadata (text, speaker, timings) embedded as JSON in the iTunes comment atom. No database is needed. The history is reconstructed by scanning the Documents directory at launch.