speech_kit 0.0.1

Native Dart bindings for Apple Speech (SpeechAnalyzer, SpeechTranscriber, AssetInventory) using Dart Build Hooks.

Speech for Dart

Native Dart bindings for Apple Speech (SpeechAnalyzer pipeline) using Dart Build Hooks.

speech_kit exposes SpeechAnalyzer, SpeechTranscriber, DictationTranscriber, SpeechDetector, and AssetInventory from Dart with a small façade—not the legacy SFSpeechRecognizer / task-based API. Native code is compiled via hooks and bridged with FFI.

Features

• Permissions — Speech recognition and microphone status / requests (native checks for usage-description keys where applicable)
• Asset inventory — AssetInventory.status, download/install, and bestAvailableAudioFormat for configured modules
• Analysis sessions — analyzeFile, analyzePcm, analyzePcmStream with optional AnalysisContext, SpeechAnalyzerOptions, and prepareToAnalyze-style preparation with progress
• Custom language model (training data) — exportCustomLanguageModelData with phrase counts, custom pronunciations, and optional PhraseCountsFromTemplatesConfig (template / compound tree)
• Custom language model (compile) — prepareCustomLanguageModel from exported training data; supportedCustomLanguagePhonemes per locale
• Dictation integration — SpeechLanguageModelPaths for SFSpeechLanguageModel.Configuration on dictation modules
• Powered by Dart Build Hooks — No Flutter dependency (pure Dart on supported hosts)

Platform Support

Platform	Support
macOS	✅
Windows	❌
Linux	❌
iOS	❌
Android	❌

macOS is the supported target for the native dylib in this release (platforms in pubspec.yaml is macOS-only). The module APIs used here require recent Apple OS releases (e.g. macOS 26+ for the current Swift bridge, consistent with iOS 26+ / visionOS 26+ for the same Speech symbols). Callers need dart:io (VM or an embedder that provides dart.library.io); non-IO configurations use stubs that throw UnsupportedError.

Installation

Add the package:

dart pub add speech_kit

From a local path:

dependencies:
  speech_kit:
    path: ../speech-kit

Example

import 'package:speech_kit/speech_kit.dart';

Future<void> main() async {
  const kit = SpeechKit();
  final speech = await kit.speechRecognitionAuthorizationStatus();
  // Request permission if needed, build SpeechModuleConfiguration list,
  // ensure assets, then analyzeFile / analyzePcm / analyzePcmStream.
}

Usage flow

1. Check permissions — speechRecognitionAuthorizationStatus() / requestSpeechRecognitionPermission() and microphone APIs as needed.
2. Describe modules — Build a List<SpeechModuleConfiguration> (transcriber, dictation, optional speech detector).
3. Assets — assetInventoryStatus / ensureAssetsInstalled; use bestAvailableAudioFormat when preparing audio.
4. Analyze — analyzeFile (or PCM / stream) with optional AnalysisContext, SpeechAnalyzerOptions, and preparation callbacks.
5. Optional: custom LM — exportCustomLanguageModelData → prepareCustomLanguageModel; attach compiled paths via dictation configuration when required.
6. Retention — Call endSpeechModelRetention when you no longer need models kept after analysis (if you used lingering / process-lifetime retention options).

For CLI samples (permission_status, asset_inventory, analyze_file), see example/README.md.

Architecture

This package uses Dart Build Hooks to compile native code and bridge Apple’s Speech APIs to Dart.

Dart layers (inward dependencies): domain (value objects, errors) → application (SpeechKit façade, SpeechAnalysisSession) → infrastructure (macOS FFI + speech_kit_no_io stub). The public barrel exports domain types and the façade.

Dart (barrel + SpeechKit)
 │
 │  FFI
 ▼
Native bridge (Swift)
 │
 ▼
Speech (Apple framework)

This keeps the Dart surface small while delegating OS work to the native library.

Example app

See the example/ directory for command-line samples and macOS bundle notes. Full instructions: example/README.md.

Roadmap

Major capability areas implemented today are listed under Features: permissions, asset inventory, file/PCM/stream analysis with context and analyzer options, custom language model export (including template-based phrase counts), compile step, supported phonemes, and dictation LM paths.

Partially exposed or not exposed in the Dart API includes anything not covered in .cursor/skills/speech-kit-api-coverage/SKILL.md. iOS FFI is not wired in the current dart:io path; macOS is the supported desktop target for this release.

Additional documentation

• Contributing — setup, tests, and PR guidelines
• Domain model — layers and value objects
• Apple Speech — Speech framework, SpeechAnalyzer, SFCustomLanguageModelData, advanced speech-to-text sample