I'm trying to create an app that can access a users Apple Music library to play music (the app will do far more than that when finished) but I am unable to generate a key. When I go to Register a New Key, it says: "There are no identifiers available that can be associated with the key" under Media Services (MusicKit, ShazamKit, Apple Music Feed). MusicKit is already checked under App Services in Certificates, Identifiers & Profiles. I've been stuck on this for two days. Please help!

I am experimenting with SpeechTranscriber and am curious if I can get quicker results when using buffered audio, rather than a file. The use case is a voice ordering experience for a restaurant. When I've been playing with it, it takes about 3 seconds for faster results and 7-8 seconds for accurate results. Is there any way to bring this down a bit? In this WWDC demo, the results appear nearly instantaneously. I'm curious how to replicate this in my app. I presume DicationTranscriber is faster, but how is siri detecting when the user stops speaking? Is it custom code, or is it using SpeechDetector? I tried using SpeechDetector with SpeechTranscriber but the detector didn't emit any results and seemed to slow down the results of SpeechTranscriber. I also assumed SpeechTranscriber makes more sense than DictationTranscriber in this use case, but want to confirm.

This is a test test test

To reduce latency in our live HLS service, we are experimenting with short segment durations (1–2 seconds). We have noticed that ABR switching occurs more frequently than expected. Looking at the console logs, variants appear to enter and leave what is referred to as a "penalty box" under conditions such as -12889 (a segment returning 0 bytes after 1.0 × target_duration) and -12888 (a playlist remaining unchanged beyond 1.5 × target_duration). Are there recommended practices to reduce this excessive switching? Specifically: Is there an API to control this penalty box behavior? Would preparing an LL-HLS stream with 1-second parts settle this down? Alternatively, would 4-second segments with a slightly smaller configuredTimeOffsetFromLive help stabilize this?

Hi, We currently deliver HDR10+ content within a composite HLS stream where Dolby Vision is signaled as a supplemental codec alongside HDR10+. Our testing on Apple TV 4K (3rd generation) indicates that playback succeeds, but we have not found a reliable way to determine whether playback is occurring in Dolby Vision or HDR10+ mode when connected to a display that supports both formats. We have also verified that the same stream plays correctly on displays that support HDR10+ but do not support Dolby Vision. However, on displays that support both HDR10+ and Dolby Vision, we are unable to determine which dynamic range format AVPlayer ultimately selects. Is there a recommended Apple API or mechanism to determine whether AVPlayer is rendering content as HDR10+, Dolby Vision, or another HDR format at runtime? For reference, below is an example variant from our master playlist: #EXT-X-STREAM-INF:BANDWIDTH=2851276,AVERAGE-BANDWIDTH=2030750,CODECS="hvc1.2.4.L90.90,mp4a.40.2",SUPPLEMENTAL-CODECS="dvh1.08.01/dv1p,hvc1.2.4.L90.90/cdm4",RESOLUTION=854x480,FRAME-RATE=24,VIDEO-RANGE=PQ,HDCP-LEVEL=TYPE-1,CHARACTERISTICS="com.dss.cbcs.hdr.hd",AUDIO="aac-128k",SUBTITLES="sub-main" Specifically, we would like to understand: How AVPlayer chooses between Dolby Vision and HDR10+ when both are available in the same variant. Whether there is a supported way to determine the selected HDR format during playback. Whether any other APIs expose this information. Any guidance would be greatly appreciated. Thank you.

Have there been any changes in macOS 27 or iOS 27 that improve real-time audio level monitoring, WidgetKit updates, Live Activities, or audio route change handling for professional monitoring applications?

Why voice processing enabled on AVAudioInputNode makes output audio noticable lower than without it and how to overcome it using voice processing enabled

In iOS 27, when a user has configured a custom AirPods EQ (three-band lows/mids/highs), does that EQ apply on top of audio output from AVAudioEngine in my app, or only to media playback through AVPlayer/MPMusicPlayerController? My app generates therapeutic frequencies (e.g. 528 Hz pure tones) where precise frequency output matters - is there any API to detect or opt out of the system AirPods EQ?

For a sleep app running 8–12 hours in background, is AVAudioSourceNode with a real-time render block more power-efficient than looping a pre-encoded audio file via AVAudioPlayerNode? I want to migrate from files to procedural synthesis but not at the cost of battery. What does Instruments / Energy Log show as the typical CPU overhead difference, and is there Apple guidance on this trade-off?

Is it possible to link a HFBluetooth input device with the output iPhone speaker while Live Listen is active?

Is it possible to port a bluetooth microphone (BluetoothHFP) to MFi hearing aids connected to an iPhone. When I try to do that the BluetoothHFP grabs input and output. When I pull the output away (BluetoothA2DP) it gives up the input.

We are working on a voice app that uses ASR/TTS on the backend and run into some difficulties in noisy environments. We have compiled the DeepFilterNet3 library into an XCFramework and are using that on the app, but it's sometimes a bit ambitious with trimming out noise and removes some of the voice. Is there any way to make use of Apple's on-device voice isolation mic mode? I see that we can detect the user's mic mode, but we cannot programmatically set it. While we could prompt the user to enable it manually, this adds a bit of friction to the user experience. Do you have any suggestions for enabling voice isolation, or for performing denoising in general?

We are using AEC in our voice app and it mostly works. However, when the experience begins we play a greeting through the speaker, and the initial few hundred milliseconds of the greeting are being captured by the inputNode. This is throwing off our ASR/TTS. For now, we've disabled audio capture while playing audio, but would prefer to be able to capture all audio with echo cancellation working. Below is some relevant code snippets. Do you have any suggestions to get AEC working more quickly? I've tried a few things like enabling voice processing before setting the audio session to active. public init() { recorderNode = engine.inputNode speakerNode = engine.outputNode mainMixerNode = engine.mainMixerNode engine.attach(audioPlayer) engine.connect( audioPlayer, to: mainMixerNode, format: nil ) playbackFormat = mainMixerNode.outputFormat(forBus: 0) } public func setupAudioSession() async throws(AudioError) { do { let audioSession = AVAudioSession.sharedInstance() try audioSession.setCategory( .playAndRecord, mode: .voiceChat, policy: .default, options: [ .defaultToSpeaker, .allowBluetoothHFP, ] ) try audioSession.setActive(true) } catch { throw .audioSessionSetupFailed(error) } do { try recorderNode.setVoiceProcessingEnabled(true) try speakerNode.setVoiceProcessingEnabled(true) } catch { throw .enableVoiceProcessingFailed(error) } }

Am I correct in my understanding that the new MusicUnderstanding is not intended to be able to support analysis of Apple Music streams via MusicKit or in other ways?

Do iOS and/or macOS support Bluetooth LC3? If yes, since what iOS/macOS version? is there any limitation and/or caveat?

I have a voice app that is both playing and recording audio. I have enabled voice processing and am setting AVAudioSession.Category to .playAndRecord and AVAudioSession.Mode to .voiceChat. When the experience first launches, we play a greeting. The first few hundred milliseconds of that greeting are being captured by the inputNode before AEC seems to start working. Is there any way to get AEC working the entire time? For now we've had to disable recording while we're playing audio, but would prefer to both play and record simultaneously. Here's some code snippets: public init(denoiseModelPath: URL? = nil) { noiseReducer = denoiseModelPath.flatMap { NoiseReducer(modelPath: $0) } recorderNode = engine.inputNode speakerNode = engine.outputNode mainMixerNode = engine.mainMixerNode engine.attach(audioPlayer) engine.connect( audioPlayer, to: mainMixerNode, format: nil ) playbackFormat = mainMixerNode.outputFormat(forBus: 0) } public func setupAudioSession() async throws(AudioError) { do { let audioSession = AVAudioSession.sharedInstance() try audioSession.setCategory( .playAndRecord, mode: .voiceChat, policy: .default, options: [ .defaultToSpeaker, .allowBluetoothHFP, ] ) try audioSession.setActive(true) } catch { throw .audioSessionSetupFailed(error) } do { try recorderNode.setVoiceProcessingEnabled(true) try speakerNode.setVoiceProcessingEnabled(true) } catch { throw .enableVoiceProcessingFailed(error) } }

We are working on a voice app that uses ASR/TTS on the backend and run into some difficulties in noisy environments. We have compiled the DeepFilterNet3 library into an XCFramework and are using that on the app, but it's sometimes a bit ambitious with trimming out noise and removes some of the voice. Is there any way to make use of Apple's on-device voice isolation mic mode? I see that we can detect the user's mic mode, but we cannot programmatically set it. While we could prompt the user to enable it manually, this adds a bit of friction to the user experience. Do you have any suggestions for enabling voice isolation, or for performing denoising in general?

Why are none of my posts showing up in the Audio Q&A? There are no errors or any useful messaging... my posts just aren't showing.

My app has a sleep timer (up to 12 hours). Can I drive a Live Activity countdown in the Dynamic Island purely from the foreground/background app process using Activity.update(), without requiring a push notification server? And does Text(timerInterval:) in SwiftUI continue counting down accurately when the app process is suspended by the OS?

Is it appropriate to use the Foundation Models framework on-device to power a natural language sound recommendation feature (e.g. user types 'I can't focus' → model returns a frequency/playlist recommendation from a predefined set)? Or is this use case better served by a custom Core ML model? What's the recommended on-device inference approach in iOS 27 for this type of structured recommendation with a small output space?