# Speech Recognition

Transcribe speech to text using Apple's Speech framework.

- Repository: https://github.com/dpearson2699/swift-ios-skills (1266 stars)
- Category: Mobile
- License: see repository
- Last updated: 2026-07-31
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add dpearson2699/swift-ios-skills --skill speech-recognition -g -a claude-code -y`
Codex: `npx skills add dpearson2699/swift-ios-skills --skill speech-recognition -g -a codex -y`
Cursor: `npx skills add dpearson2699/swift-ios-skills --skill speech-recognition -g -a cursor -y`
Gemini CLI: `npx skills add dpearson2699/swift-ios-skills --skill speech-recognition -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add dpearson2699/swift-ios-skills`

## Description

Transcribe speech to text using Apple's Speech framework. Use when implementing live microphone transcription with AVAudioEngine, recognizing recorded audio files, handling speech and microphone authorization, choosing on-device vs server-backed SFSpeechRecognizer behavior, or adopting SpeechAnalyzer, SpeechTranscriber, DictationTranscriber, AssetInventory, and async result streams on iOS 26+.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Speech Recognition

Transcribe live and pre-recorded audio to text using Apple's Speech framework.
Covers `SpeechAnalyzer` / `SpeechTranscriber` (iOS 26+) and
`SFSpeechRecognizer` (iOS 10+) fallback guidance.

**Scope boundary:** Use this skill for speech-to-text recognition, speech
authorization, microphone capture plumbing, and result handling. Hand off text
analysis, language identification after transcription, sentiment, embeddings,
and translation to `natural-language`; hand off audio playback UI to `avkit`;
hand off summarization or generation over transcripts to `apple-on-device-ai`.

## Contents

- [SpeechAnalyzer Strategy (iOS 26+)](#speechanalyzer-strategy-ios-26)
- [SFSpeechRecognizer Setup](#sfspeechrecognizer-setup)
- [Authorization](#authorization)
- [Live Microphone Transcription](#live-microphone-transcription)
- [Pre-Recorded Audio File Recognition](#pre-recorded-audio-file-recognition)
- [On-Device vs Server Recognition](#on-device-vs-server-recognition)
- [Handling Results](#handling-results)
- [Common Mistakes](#common-mistakes)
- [Review Checklist](#review-checklist)
- [References](#references)

## SpeechAnalyzer Strategy (iOS 26+)

Use `SpeechAnalyzer` for modern iOS 26+ speech analysis, especially long-form
recordings, live transcription, time-indexed transcripts, and fully on-device
flows. Keep `SFSpeechRecognizer` for iOS 10+ deployment targets, server-backed
locale coverage, or existing callback/delegate implementations.

Read [SpeechAnalyzer patterns](references/speechanalyzer-patterns.md) when
implementing an iOS 26+ transcription pipeline, model asset handling, volatile
results, or file/buffer examples.

### SpeechAnalyzer setup checklist

The rest: https://github.com/dpearson2699/swift-ios-skills/blob/HEAD/skills/speech-recognition/SKILL.md