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
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.
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 when
implementing an iOS 26+ transcription pipeline, model asset handling, volatile
results, or file/buffer examples.
SpeechAnalyzer setup checklist
Choose the module:
SpeechTranscriber for the newer general-purpose on-device model.
DictationTranscriber when SpeechTranscriber is unavailable for the
current device or locale and dictation-compatible support is acceptable.
SpeechDetector only in conjunction with a transcriber when voice
activity detection is worth the accuracy/power tradeoff.
Check support before creating the session:
SpeechTranscriber.isAvailable
SpeechTranscriber.supportedLocale(equivalentTo:)
SpeechTranscriber.installedLocales / supportedLocales when showing
language choices.
Pick a documented preset:
.transcription for basic accurate transcription.
.progressiveTranscription for live UI updates.
.timeIndexedProgressiveTranscription when playback highlighting needs
audioTimeRange.
Install required assets with AssetInventory.assetInstallationRequest.
Convert live audio buffers to
SpeechAnalyzer.bestAvailableAudioFormat(compatibleWith:) before yielding
AnalyzerInput.
Consume module results from their AsyncSequence in a separate task.
Finish explicitly with finalizeAndFinish(through:),
finalizeAndFinishThroughEndOfInput(), or cancelAndFinishNow().
Do not use an offlineTranscription preset; Apple does not document one.
Finishing an AsyncStream input sequence does not finish the analyzer session.
SFSpeechRecognizer Setup
Creating a recognizer with locale
import Speech
// Default locale (user's current language)
let recognizer = SFSpeechRecognizer()
// Specific locale
let recognizer = SFSpeechRecognizer(locale: Locale(identifier: "en-US"))
// Check if recognition is available for this locale
guard let recognizer, recognizer.isAvailable else {
print("Speech recognition not available")
return
}
Monitoring availability changes
final class SpeechManager: NSObject, SFSpeechRecognizerDelegate {
private let recognizer = SFSpeechRecognizer()!
override init() {
super.init()
recognizer.delegate = self
}
func speechRecognizer(
_ speechRecognizer: SFSpeechRecognizer,
availabilityDidChange available: Bool
) {
// Update UI — disable record button when unavailable
}
}
Authorization
Request both speech recognition and microphone permissions before starting
live transcription. Add these keys to Info.plist:
NSSpeechRecognitionUsageDescription
NSMicrophoneUsageDescription
import Speech
import AVFoundation
func requestPermissions() async -> Bool {
let speechStatus = await withCheckedContinuation { continuation in
SFSpeechRecognizer.requestAuthorization { status in
continuation.resume(returning: status)
}
}
guard speechStatus == .authorized else { return false }
let micStatus: Bool
if #available(iOS 17, *) {
micStatus = await AVAudioApplication.requestRecordPermission()
} else {
micStatus = await withCheckedContinuation { continuation in
AVAudioSession.sharedInstance().requestRecordPermission { granted in
continuation.resume(returning: granted)
}
}
}
return micStatus
}
Live Microphone Transcription
The standard pattern: AVAudioEngine captures microphone audio → buffers are
appended to SFSpeechAudioBufferRecognitionRequest → results stream in.
import Speech
import AVFoundation
final class LiveTranscriber {
private let recognizer = SFSpeechRecognizer(locale: Locale(identifier: "en-US"))!
private let audioEngine = AVAudioEngine()
private var recognitionRequest: SFSpeechAudioBufferRecognitionRequest?
private var recognitionTask: SFSpeechRecognitionTask?
func startTranscribing() throws {
// Cancel any in-progress task
recognitionTask?.cancel()
recognitionTask = nil
// Configure audio session
let audioSession = AVAudioSession.sharedInstance()
try audioSession.setCategory(.record, mode: .measurement, options: .duckOthers)
try audioSession.setActive(true, options: .notifyOthersOnDeactivation)
// Create request
let request = SFSpeechAudioBufferRecognitionRequest()
request.shouldReportPartialResults = true
self.recognitionRequest = request
// Start recognition task
recognitionTask = recognizer.recognitionTask(with: request) { result, error in
if let result {
let text = result.bestTranscription.formattedString
print("Transcription: \(text)")
if result.isFinal {
self.stopTranscribing()
}
}
if let error {
print("Recognition error: \(error)")
self.stopTranscribing()
}
}
// Install audio tap
let inputNode = audioEngine.inputNode
let recordingFormat = inputNode.outputFormat(forBus: 0)
inputNode.installTap(onBus: 0, bufferSize: 1024, format: recordingFormat) {
buffer, _ in
request.append(buffer)
}
audioEngine.prepare()
try audioEngine.start()
}
func stopTranscribing() {
audioEngine.stop()
audioEngine.inputNode.removeTap(onBus: 0)
recognitionRequest?.endAudio()
recognitionRequest = nil
recognitionTask?.cancel()
recognitionTask = nil
}
}
Pre-Recorded Audio File Recognition
Use SFSpeechURLRecognitionRequest for audio files on disk:
func transcribeFile(at url: URL) async throws -> String {
guard let recognizer = SFSpeechRecognizer(), recognizer.isAvailable else {
throw SpeechError.unavailable
}
let request = SFSpeechURLRecognitionRequest(url: url)
request.shouldReportPartialResults = false
return try await withCheckedThrowingContinuation { continuation in
var didResume = false
recognizer.recognitionTask(with: request) { result, error in
guard !didResume else { return }
if let error {
didResume = true
continuation.resume(throwing: error)
} else if let result, result.isFinal {
didResume = true
continuation.resume(
returning: result.bestTranscription.formattedString
)
}
}
}
}
On-Device vs Server Recognition
SFSpeechRecognizer can use on-device recognition for supported locales on
iOS 13+. If supportsOnDeviceRecognition is false, the recognizer requires a
network connection. requiresOnDeviceRecognition only has effect when the
recognizer supports it.
let recognizer = SFSpeechRecognizer(locale: Locale(identifier: "en-US"))!
// Check if on-device is supported for this locale
if recognizer.supportsOnDeviceRecognition {
let request = SFSpeechAudioBufferRecognitionRequest()
request.requiresOnDeviceRecognition = true // Force on-device
}
SFSpeechRecognizer requests may still be a poor fit for long-form capture.
Apple documents a roughly one-minute task limit for speech recognition and
other service limits. For long recordings on iOS 26+, prefer SpeechAnalyzer;
otherwise chunk or restart recognition before the limit and preserve transcript
state across tasks.
Handling Results
Partial vs final results
With shouldReportPartialResults, replace the displayed partial transcript until SFSpeechRecognitionResult.isFinal commits it. This is separate from SpeechTranscriber.Result.isFinal, whose volatile attributed range must be replaced by the final result for that range. The live example and references/speechanalyzer-patterns.md contain the canonical loops.
Accessing alternative transcriptions and confidence
recognizer.recognitionTask(with: request) { result, error in
guard let result else { return }
// Best transcription
let best = result.bestTranscription
// All alternatives (sorted by confidence, descending)
for transcription in result.transcriptions {
for segment in transcription.segments {
print("\(segment.substring): \(segment.confidence)")
}
}
}
Adding punctuation (iOS 16+)
let request = SFSpeechAudioBufferRecognitionRequest()
request.addsPunctuation = true
Contextual strings
Improve recognition of domain-specific terms:
let request = SFSpeechAudioBufferRecognitionRequest()
request.contextualStrings = ["SwiftUI", "Xcode", "CloudKit"]
Common Mistakes
Mistake
Fix
Live audio requests only speech authorization
Require both speech and microphone permission.
Recognizer availability is checked once
Observe delegate availability changes and model loss of service.
Final/error/rollover paths perform different cleanup
Use one stopTranscribing() owner for engine stop, tap removal, endAudio, and task cancellation.
On-device mode is forced for every locale
Check supportsOnDeviceRecognition and provide a fallback.
One SFSpeechRecognizer task is used for long-form capture
Prefer SpeechAnalyzer on iOS 26+ or roll bounded segments while preserving committed transcript.
Finishing analyzer input is treated as session completion
Explicitly finalize through the last sample or cancel-and-finish.
Volatile SpeechAnalyzer results are appended
Replace the volatile range until a final result commits it.
A second recognition task starts before the first ends
Cancel/finish the active task and complete cleanup before replacement.