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Sometimes. If recognition genuinely runs on your device, the transcription step does not need to upload your audio or transcript to a speech service. However, “offline” is not a universal privacy guarantee. Operating-system settings, recognizer implementations, language downloads, assistants, telemetry, and the app that receives the text can all change what travels over the network.
To determine what happens, inspect the exact feature rather than relying on its marketing label: where recognition runs, whether audio leaves the device, whether transcript text is synchronized afterward, and whether setup or optional features require a connection.
What “offline speech recognition” actually means
Speech-to-text has several separate stages. Treating them as one process is the main reason privacy explanations become misleading.
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- Capture and activation: a microphone records speech, while a keyboard, assistant, accessibility service, or other app decides when to listen.
- Recognition: a speech model converts audio into words. This inference can happen on the device or on a remote server.
- Transcript handling: the resulting text is inserted into an app, saved, synchronized, analyzed, or sent to another service.
“Offline recognition” primarily describes the second stage. It does not prove that the device made no connection to download a model, that the microphone service never communicates, or that the destination app will keep the resulting text local.
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A local recognizer can therefore produce a transcript without uploading the recording, while the notes app, keyboard, cloud backup, assistant, or collaboration tool immediately sends the text elsewhere. Conversely, an app may describe itself as offline for normal use but still contact a server for initial setup, updates, diagnostics, account functions, or an online language.
When audio and transcripts stay local
Audio and transcript text can remain on the device when all of the following are true:
- The selected recognizer has a local speech model and performs inference on the device.
- The required language or model files are already installed.
- The feature’s privacy documentation says audio is not uploaded for recognition.
- No separate assistant, sync service, or receiving app transmits the transcript.
- Optional online functions, diagnostics, and account services are disabled or unavailable.
That is a configuration-specific conclusion, not a property shared by every feature called “offline.” A strict no-network requirement should be verified on the exact operating-system version, language, account, and app combination you intend to use.
Platform comparison
| Platform or feature | Where recognition can run | What the documentation says about network traffic | Important qualification |
|---|---|---|---|
| Apple on-device Dictation | On the device | Apple says processing is completely offline and provides an indication in Siri or Keyboard settings when speech is processed on device. | This does not make every Siri or voice feature local; requests that are not processed on device may go to Apple servers. |
| Windows device-based speech recognition | On the device | Microsoft states that no voice data is sent to Microsoft when device-based recognition is used. | Online speech recognition instead sends voice data to Microsoft’s cloud service for recognition and transcription. |
| Android recognizer API | Depends on the recognizer implementation | EXTRA_PREFER_OFFLINE is only a preference. The default permits either network or offline engines. |
An implementation may ignore the preference, so the API flag is not proof that audio stayed local. |
| Google Voice Access | Primarily on the device | Google says it primarily processes audio on device and requires downloaded language packs for use without a network connection. | Configuration and system language can cause audio to be sent to Google servers. |
| Google Cloud Speech-to-Text | Google’s cloud service | Audio is sent to the service and recognition results are returned as transcripts. | Cloud retention and logging terms differ by request type and data-logging settings; this is not the same as on-device Android recognition. |
| LocalWhisper desktop app | On the local computer after setup | The vendor says a speech model is downloaded on first launch, after which transcription works offline. | This is a vendor statement about that app, not an independent audit or evidence about other transcription software. |
Apple: Dictation is not the same as every Siri request
On-device Dictation
Apple’s feature privacy documentation says on-device Dictation “helps protect your privacy further by performing all processing completely offline.” Apple also directs users to Siri or Keyboard settings for an indication that speech is processed on the device and not sent to Apple.
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When that indication is present and the needed language resources are installed, the recognition operation itself can occur without sending the recorded speech to Apple. The text still belongs to the app into which you dictated. If that app syncs documents, backs up data, or invokes an online writing or assistant feature, the transcript can leave the device afterward.
Siri and other voice features
Apple distinguishes on-device processing from Siri requests that require servers. A spoken command may need remote processing when it involves a service, account information, or a capability unavailable on the device. Do not infer Siri’s network behavior from the privacy statement for Dictation, and do not treat an Apple device’s offline Dictation indicator as a blanket promise for all microphones or assistants.
Windows: an explicit local-versus-online setting
Microsoft’s Windows privacy documentation makes a direct distinction between device-based and online speech recognition. With device-based recognition selected and online speech recognition turned off, Microsoft says: “No voice data is sent to Microsoft.”
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Microsoft’s support information covers Windows 10 and Windows 11. Windows 10 support ended on October 14, 2025; that date does not automatically change how a particular installation behaves, but it makes the current settings and documentation especially important for systems that remain on Windows 10.
Android: an offline preference is not a guarantee
The recognizer API
Android exposes EXTRA_PREFER_OFFLINE for applications that request speech recognition. The API reference describes it as an optional preference. Its default is false, which allows either a network-based or offline engine, and the recognizer implementation may ignore the preference altogether.
As a result, an app that sets the flag cannot by itself promise that audio will stay on the phone. The selected recognition service, installed language data, device manufacturer, Android release, and network availability can all affect the result. Developers who require a local-only path must identify and control the actual recognizer implementation rather than merely setting the extra.
How to check an Android app
- Identify the exact app and speech feature, such as keyboard dictation, an accessibility service, or an in-app microphone.
- Open that feature’s speech, language, privacy, or data settings and look for an explicit on-device or offline mode.
- Confirm that the language pack or model is downloaded before disconnecting the phone.
- Check which recognition service the app invokes; the Android preference does not establish that every service is local.
- Review the destination app’s synchronization, backup, and sharing controls for the text produced.
Google Voice Access: mostly local, with conditions
Google describes Voice Access as primarily processing audio on the device. For use without a network connection, Google requires downloaded language packs. That requirement matters: an offline-capable feature can still need a network during setup to obtain the model or language resources.
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Google also notes that configuration and the system language can affect whether audio is sent to Google servers. Therefore, “Voice Access works offline” should be read as a conditional statement about a properly configured language and device, not as a promise that every Voice Access session or related Google speech feature is local.
Google’s statement about federated learning—that speech models can be trained without sending audio data to Google’s servers—describes a particular training approach. It is not evidence that every Google speech feature performs recognition offline.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Cloud transcription is a different data flow
Google Cloud Speech-to-Text is explicitly a cloud API. An application sends audio to the service, the service performs recognition, and transcript results are returned. That is online recognition even if the application later caches the transcript or lets you work without a connection.
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For a cloud API, ask four separate questions: Is the audio retained? Is the returned transcript retained? What request metadata is logged? Which optional data-logging or model-improvement setting is enabled? The answer to one does not answer the others.
Model downloads and “offline after setup”
Offline operation often begins with an online download. A speech model or language pack may be hundreds of megabytes, and the application may not function until it is installed. That initial connection is different from uploading speech for recognition, but it is still network traffic that matters in a high-security environment.
LocalWhisper’s documentation illustrates this pattern: the vendor says its app downloads a model on first launch and then transcribes offline. This establishes a setup dependency for that app, not a general rule for local transcription products. Check whether updates, additional languages, crash reports, licensing checks, or telemetry also require a connection.
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The receiving app can send the transcript
Even when no audio leaves the device, the text may. Common examples include:
- A keyboard inserts dictated text into an email composer that syncs drafts.
- A notes app uploads the new note to a cloud account.
- An assistant sends the command and its context to a remote service.
- A browser form submits the text as soon as the user taps a button.
- An accessibility tool forwards recognized commands to an online automation service.
To assess this stage, inspect the destination app’s sync, backup, account, sharing, and analytics controls. Also consider automatic clipboard history or cross-device copy features, which can replicate text even when the speech recognizer itself is local.
A practical verification checklist
- Write down the exact configuration. Record the operating system and version, app name and version, recognition language, account state, and whether an assistant or keyboard is involved.
- Find the feature-specific privacy statement. Look for “on-device,” “device-based,” or an explicit statement about audio being sent. Do not rely on the single word “offline.”
- Install models before testing. Download language packs while connected, then verify that the feature still works with networking disabled.
- Check the recognition service. On Android especially, identify the implementation behind the API request;
EXTRA_PREFER_OFFLINEis not conclusive. - Separate audio from text. Determine whether the transcript is inserted into a syncing app, sent to an assistant, or uploaded by backup software.
- Review optional traffic. Check telemetry, diagnostics, update checks, account verification, and online-only commands.
- Apply network isolation if the requirement is strict. Airplane mode, firewall rules, or a segmented network can be used as a separate verification step for the exact device and configuration.
No general statistic establishes how often products marketed as offline send audio or transcripts. The reliable answer is product-specific: confirm the documented behavior and configuration for the feature you intend to use.
Bottom line
Offline speech recognition can keep recognition audio and the resulting transcript on the device, but the label alone is insufficient. Apple documents fully offline on-device Dictation; Windows documents a device-based mode that sends no voice data to Microsoft; Android’s offline preference can be ignored; Google Voice Access is conditional on language and configuration; and cloud speech APIs necessarily transmit audio for recognition. Check the exact feature, model downloads, recognizer implementation, and receiving app before treating a setup as truly no-network.
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