Hello, I am testing the sample project provided here: Bringing advanced speech-to-text capabilities to your app. On both macOS 26.0 beta and iOS 26.0 beta, the app crashes immediately on launch with a dyld "Symbol not found" error related to FoundationModels.framework. It feels like this may be related to testing primarily on newer Apple Silicon devices, as I am seeing consistent crashes on an Intel MacBook and on an older iPhone device. I would appreciate any insight, confirmation, or guidance on whether this is a known limitation or if there is a workaround. Is it planned to be resolved soon? Environment macOS: Device: MacBook Pro (Intel) Processor: 2 GHz Quad-Core Intel Core i5 Graphics: Intel Iris Plus Graphics 1536 MB Memory: 16 GB 3733 MHz LPDDR4X OS: macOS Tahoe Version 26.0 Beta (25A5338b) iOS: Device: iPhone 11 Model Number: MHDD3HN/A OS: iOS 26.0 Xcode: Version: 26.0 beta 3 (17A5276g) Crash (macOS) Abort signal received. Excerpt from crash dump: dyld`__abort_with_payload: 0x7ff80e3ad4a0 <+0>: movl $0x2000209, %eax 0x7ff80e3ad4a5 <+5>: movq %rcx, %r10 0x7ff80e3ad4a8 <+8>: syscall -> 0x7ff80e3ad4aa <+10>: jae 0x7ff80e3ad4b4 Console: dyld[9819]: Symbol not found: _$s16FoundationModels20LanguageModelSessionC5model10guardrails5tools12instructionsAcA06SystemcD0C_AC10GuardrailsVSayAA4Tool_pGAA12InstructionsVSgtcfC Referenced from: /Users/userx/Library/Developer/Xcode/DerivedData/SwiftTranscriptionSampleApp-*/Build/Products/Debug/SwiftTranscriptionSampleApp.app/Contents/MacOS/SwiftTranscriptionSampleApp.debug.dylib Expected in: /System/Library/Frameworks/FoundationModels.framework/Versions/A/FoundationModels Crash (iOS) Abort signal received. Excerpt from crash dump: dyld`__abort_with_payload: 0x18f22b4b0 <+0>: mov x16, #0x209 0x18f22b4b4 <+4>: svc #0x80 -> 0x18f22b4b8 <+8>: b.lo 0x18f22b4d8 Console dyld[2080]: Symbol not found: _$s16FoundationModels20LanguageModelSessionC5model10guardrails5tools12instructionsAcA06SystemcD0C_AC10GuardrailsVSayAA4Tool_pGAA12InstructionsVSgtcfC Referenced from: /private/var/containers/Bundle/Application/.../SwiftTranscriptionSampleApp.app/SwiftTranscriptionSampleApp.debug.dylib Expected in: /System/Library/Frameworks/FoundationModels.framework/FoundationModels Question Is this crash expected on Intel Macs and older iPhone models with the beta SDKs? Is there an official statement on whether macOS 26.x releases support Intel, or it exists only until macOS 26.1? Any suggested workarounds for testing this sample project on current hardware? Is this a known limitation for the 26.0 beta, and if so, should we expect a fix in 26.0 or only in subsequent releases? Attaching screenshots for reference. Thank you in advance.

We are a research team conducting a study collecting subject's SensorKit speech data, and we've encountered some questions we couldn't resolve ourselves or by looking up the online SensorKit documentation: Microphone Activation: In general, how is the microphone being turned on to capture a speech session? And how was each session determined to be an independent session? Negative Values: In the speech classification data, there are entries where some of the start and end values are negative (see screenshot below). How should we interpret and handle these values? Is it safe to filter them out? Duplicated sessions: From the same screenshot you can see there are multiple session identifiers linked to the same subject with the same timestamp - what does this represent? Another Negative Values: The same question for speech recognition data's average pause duration, what does the -1 mean and should we remove them as well? (Note that these screenshot got rid of subject IDs for privacy purposes but each screenshot was from one subject.) We greatly appreciate your time and help.

Using the official SwiftTranscriptionSampleApp from WWDC 2025, speech transcription takes 14+ seconds from audio input to first result, making it unusable for real-time applications. Environment iOS: 26.0 Beta Xcode: Beta 5 Device: iPhone 16 pro Sample App: Official Apple SwiftTranscriptionSampleApp from WWDC 2025 Configuration Tested Locale: en-US (properly allocated with AssetInventory.allocate(locale:)) and es-ES Setup: All optimizations applied (preheating, high priority, model retention) I started testing in my own app to replace SFSpeech API and include speech detection but after long fights with documentation (this part is quite terrible TBH) I tested the example (https://developer.apple.com/documentation/speech/bringing-advanced-speech-to-text-capabilities-to-your-app) and saw same results. I added some logs to check the specific time: 🎙️ [20:30:41.532] ✅ Analyzer started successfully - ready to receive audio! 🎙️ [20:30:41.532] Listening for transcription results... 🎙️ [20:30:56.342] 🚀 FIRST TRANSCRIPTION RESULT after 14.810s: 'Hello' (isFinal: false) Questions Is this expected performance for iOS 26 Beta, because old SFSpeech is far faster? Are there additional optimization steps for SpeechTranscriber? Should we expect significant performance improvements in later betas?

I started playing which transcription of audio files on macOS today, latest beta of Xcode and latest beta of Tahoe. Transcription itself works really well, but for some reason the majority of the results contain no audioTimeRange. I got 22 single-word results with time ranges, spread out all over total file of 53 minutes. Is there something I can do to improve this? To my understanding, I have followed sample code and instructions very closely, but the SwiftTranscriptionSampleApp and other examples I've seen lead me to believe I should be getting a lot more time ranges than I actually do.

I'm working in Swift/SwiftUI, running XCode 16.3 on macOS 15.4 and I've seen this when running in the iOS simulator and in a macOS app run from XCode. I've also seen this behaviour with 3 different audio files. Nothing in the documentation says that the speechRecognitionMetadata property on an SFSpeechRecognitionResult will be nil until isFinal, but that's the behaviour I'm seeing. I've stripped my class down to the following: private var isAuthed = false // I call this in a .task {} in my SwiftUI View public func requestSpeechRecognizerPermission() { SFSpeechRecognizer.requestAuthorization { authStatus in Task { self.isAuthed = authStatus == .authorized } } } public func transcribe(from url: URL) { guard isAuthed else { return } let locale = Locale(identifier: "en-US") let recognizer = SFSpeechRecognizer(locale: locale) let recognitionRequest = SFSpeechURLRecognitionRequest(url: url) // the behaviour occurs whether I set this to true or not, I recently set // it to true to see if it made a difference recognizer?.supportsOnDeviceRecognition = true recognitionRequest.shouldReportPartialResults = true recognitionRequest.addsPunctuation = true recognizer?.recognitionTask(with: recognitionRequest) { (result, error) in guard result != nil else { return } if result!.isFinal { //speechRecognitionMetadata is not nil } else { //speechRecognitionMetadata is nil } } } } Further, and this isn't documented either, the SFTranscriptionSegment values don't have correct timestamp and duration values until isFinal. The values aren't all zero, but they don't align with the timing in the audio and they change to accurate values when isFinal is true. The transcription otherwise "works", in that I get transcription text before isFinal and if I wait for isFinal the segments are correct and speechRecognitionMetadata is filled with values. The context here is I'm trying to generate a transcription that I can then highlight the spoken sections of as audio plays and I'm thinking I must be just trying to use the Speech framework in a way it does not work. I got my concept working if I pre-process the audio (i.e. run it through until isFinal and save the results I need to json), but being able to do even a rougher version of it 'on the fly' - which requires segments to have the right timestamp/duration before isFinal - is perhaps impossible?

During testing the “Bringing advanced speech-to-text capabilities to your app” sample app demonstrating the use of iOS 26 SpeechAnalyzer, I noticed that the language model for the English locale was presumably already downloaded. Upon checking the documentation of AssetInventory, I found out that indeed, the language model can be preinstalled on the system. Can someone from the dev team share more info about what assets are preinstalled by the system? For example, can we safely assume that the English language model will almost certainly be already preinstalled by the OS if the phone has the English locale?

i tried combine speech detector and speech transciber to anlayzer. but speech detector is not speech module. please help me

I have Xcode 16 and am setting everything to a minimum target deployment to 17.5, and am using import Speech Never the less, Xcode doesn't can't find it. At ChatGPT's urging I tried going back to Xcode 15.3, but that won't work with Sequoia Am I misunderstanding something? Here's how I am trying to use it: if templateItems.isEmpty { templateItems = dbControl?.getAllItems(templateName: templateName) ?? [] items = templateItems.compactMap { $0.itemName?.components(separatedBy: " ") }.flatMap { $0 } let phrases = extractContextualWords(from: templateItems) Task { do { // 1. Get your items and extract words templateItems = dbControl?.getAllItems(templateName: templateName) ?? [] let phrases = extractContextualWords(from: templateItems) // 2. Build the custom model and export it let modelURL = try await buildCustomLanguageModel(from: phrases) // 3. Prepare the model (STATIC method) try await SFSpeechRecognizer.prepareCustomLanguageModel(at: modelURL) // ✅ Ready to use in recognition request print("✅ Model prepared at: \(modelURL)") // Save modelURL to use in Step 5 (speech recognition) // e.g., self.savedModelURL = modelURL } catch { print("❌ Error preparing model: \(error)") } } }

I'm experimenting with the new SpeechTranscriber in macOS/iOS 26, transcribing speech from a prerecorded mp4 file. Speed and quality are amazing! I've told the transcriber to include time indexes. Each run is always exactly one word, which can be very useful. When I look at the indexes the end of one run is always identical to the start of the next run, even if there's a pause. I'd like to identify pauses, perhaps to generate something like phrases for subtitling. With each run of text going into the next I can't do this, other than using punctuation - which might be rather rough. Any suggestions on detecting pauses, or getting that kind of metadata from the transcriber? Here's a short sample, showing each run with the start, end, and characters in the run: 105.9 --> 107.04 I 107.04 --> 107.16 think 107.16 --> 108.0 more 108.0 --> 108.42 lighting 108.42 --> 108.6 is 108.6 --> 108.72 definitely 108.72 --> 109.2 needed, 109.2 --> 109.92 downtown. 109.98 --> 110.4 My 110.4 --> 110.52 only 110.52 --> 110.7 question 110.7 --> 111.06 is, 111.06 --> 111.48 poll 111.48 --> 111.78 five, 111.78 --> 111.84 that 111.84 --> 112.08 you're 112.08 --> 112.38 increasing 112.38 --> 112.5 the 112.5 --> 113.34 50,000? 113.4 --> 113.58 Where 113.58 --> 113.88 exactly