/speech-recognition

SpeechAnalyzer Patterns

Use this reference when implementing iOS 26+ speech-to-text with SpeechAnalyzer, SpeechTranscriber, DictationTranscriber, SpeechDetector, or AssetInventory.

Contents

• Choosing Modules
• Preparing Assets
• Transcribing Files
• Live Audio
• Handling Results
• Finishing Sessions
• References

Choosing Modules

Prefer SpeechTranscriber for the newer general-purpose on-device model. Before building UI around it, check both device and locale support:

guard SpeechTranscriber.isAvailable,
      let locale = SpeechTranscriber.supportedLocale(equivalentTo: Locale.current)
else {
    // Disable the feature or try DictationTranscriber for compatible devices/locales.
    return
}

Use documented presets only:

• .transcription for basic accurate transcription.
• .transcriptionWithAlternatives for editing suggestions.
• .timeIndexedTranscriptionWithAlternatives for audio-time metadata plus alternatives.
• .progressiveTranscription for low-latency live UI updates.
• .timeIndexedProgressiveTranscription for live UI updates with time ranges.

Use DictationTranscriber when SpeechTranscriber is unavailable and the app can accept dictation-model behavior. Add SpeechDetector only with a transcriber module, and only when voice activity detection is worth the risk of dropping speech-like audio.

Preparing Assets

SpeechAnalyzer modules require model assets. The system installs and shares them outside the app bundle, but the app must request installation for the module configuration it plans to use.

let transcriber = SpeechTranscriber(locale: locale, preset: .transcription)

if let request = try await AssetInventory.assetInstallationRequest(
    supporting: [transcriber]
) {
    try await request.downloadAndInstall()
}

For language pickers, use installedLocales, supportedLocales, and AssetInventory.status(forModules:) to distinguish installed, downloadable, and unsupported choices. The app has a limited number of locale reservations; release unused reservations with AssetInventory.release(reservedLocale:).

Transcribing Files

For files, let the analyzer convert the file to a compatible format and finish the session after the file is consumed.

func transcribeFile(at url: URL, locale: Locale) async throws -> AttributedString {
    guard let supportedLocale = SpeechTranscriber.supportedLocale(equivalentTo: locale) else {
        throw SpeechError.unsupportedLocale
    }

    let transcriber = SpeechTranscriber(
        locale: supportedLocale,
        preset: .transcription
    )

    if let request = try await AssetInventory.assetInstallationRequest(
        supporting: [transcriber]
    ) {
        try await request.downloadAndInstall()
    }

    let analyzer = SpeechAnalyzer(modules: [transcriber])
    async let transcript = transcriber.results.reduce(into: AttributedString()) {
        text, result in
        text.append(result.text)
    }

    let file = try AVAudioFile(forReading: url)
    let lastSampleTime = try await analyzer.analyzeSequence(from: file)
    if let lastSampleTime {
        try await analyzer.finalizeAndFinish(through: lastSampleTime)
    } else {
        try analyzer.cancelAndFinishNow()
    }

    return try await transcript
}

Live Audio

For live audio, create an AsyncStream<AnalyzerInput>, convert microphone buffers to the analyzer-compatible format, yield them, and consume results in a separate task.

let transcriber = SpeechTranscriber(
    locale: locale,
    preset: .timeIndexedProgressiveTranscription
)
let analyzer = SpeechAnalyzer(modules: [transcriber])
let audioFormat = await SpeechAnalyzer.bestAvailableAudioFormat(
    compatibleWith: [transcriber]
)
let (inputSequence, inputBuilder) = AsyncStream.makeStream(of: AnalyzerInput.self)

// In the audio-engine tap, convert each AVAudioPCMBuffer to audioFormat first.
inputBuilder.yield(AnalyzerInput(buffer: convertedBuffer))

Use AVAudioConverter or an existing project audio pipeline for the conversion. Do not feed arbitrary input-node formats directly unless they already match a compatible analyzer format.

Handling Results

SpeechTranscriber.Result.text is an AttributedString. Time-indexed presets include audio time range attributes that can drive playback highlighting.

When using progressive presets, volatile results may be replaced by later final results. Keep volatile display state separate so the UI does not duplicate text.

for try await result in transcriber.results {
    if result.isFinal {
        volatileTranscript = AttributedString()
        finalizedTranscript.append(result.text)
    } else {
        volatileTranscript = result.text
    }
}

Finishing Sessions

The analyzer can only analyze one input sequence at a time. Ending your stream does not finish the analyzer session; call a finish or cancel method.

Use:

• finalizeAndFinish(through:) after analyzeSequence(_:) returns a final sample time.
• finalizeAndFinishThroughEndOfInput() after autonomous start(inputSequence:).
• cancelAndFinishNow() for immediate cancellation.

After the session finishes, result streams terminate and most analyzer methods no longer accept new work. Create a new analyzer for a new finished session.

References

• SpeechAnalyzer
• SpeechTranscriber
• SpeechTranscriber.Preset
• DictationTranscriber
• SpeechDetector
• AssetInventory
• WWDC25: Bring advanced speech-to-text to your app with SpeechAnalyzer