Data Privacy Policies of Cloud Speech-to-Text Services: A Complete Comparison

Why Comparing Cloud STT Privacy Policies Matters

Cloud-based speech-to-text services are embedded in nearly everything: virtual assistants, customer support platforms, transcription tools, accessibility features, and smart devices. Millions of hours of human speech are processed by cloud servers every day. Yet most users have little understanding of what happens to their voice data once it leaves their device.

Each major cloud provider — Google, Amazon, Microsoft, and Apple — handles voice data differently. Their privacy policies, data retention practices, opt-out mechanisms, and regulatory compliance postures vary significantly. For businesses choosing a speech-to-text provider, and for individuals who care about their privacy, these differences matter enormously.

This article provides a detailed, side-by-side comparison of how the four major cloud speech-to-text providers handle your voice data, and explains why a growing number of users are choosing to leave the cloud behind entirely.

The Four Major Cloud Speech-to-Text Services

Before comparing policies, let us briefly describe each service:

Google Cloud Speech-to-Text — Part of Google Cloud Platform. Supports 125+ languages. Used by enterprise applications and Android devices. See our in-depth analysis of Google's privacy practices.
Amazon Transcribe — Part of Amazon Web Services (AWS). Offers real-time and batch transcription. Widely used in call center analytics and content processing.
Microsoft Azure Speech — Part of Microsoft Azure Cognitive Services. Integrated into Microsoft 365, Teams, and enterprise applications. Supports custom speech models.
Apple Dictation — Built into macOS, iOS, iPadOS, and watchOS. Uses a hybrid approach with some on-device and some cloud processing. For more details, read our Apple Dictation comparison.

Privacy Policy Comparison Table

The following table summarizes the key privacy characteristics of each service as of early 2026:

Data Transmission

Google — All audio sent to Google servers for processing. Encrypted in transit via TLS.
Amazon — All audio sent to AWS servers. Encrypted in transit. Option for VPC endpoints for private connectivity.
Microsoft — Audio sent to Azure servers by default. Offers a connected container option that processes audio on-premises while still requiring cloud connectivity for billing.
Apple — Hybrid model. Some languages processed on-device (especially on newer hardware), others sent to Apple servers. Users often cannot tell which mode is active.

Data Retention

Google — Audio may be retained for service improvement unless data logging is explicitly disabled. Retention period unspecified for logged data. Transcription results are not stored by default.
Amazon — Audio processed by Amazon Transcribe may be stored and used to improve the service unless you opt out via AWS AI Service Opt-Out Policy. Content is retained for an unspecified period.
Microsoft — Audio data is retained for up to 30 days by default for troubleshooting. Custom Speech models may retain training data indefinitely. Microsoft states they do not use customer data to improve base models without explicit permission.
Apple — Apple states that Siri and dictation data is anonymized using random identifiers and retained for up to 6 months for improvement, then up to 2 years in anonymized form. Users can opt out of sharing.

Human Review of Audio

Google — Has confirmed human review of audio snippets for quality improvement. Tightened policies after 2019 backlash. Review occurs unless customers opt out.
Amazon — Has confirmed that human reviewers may listen to Amazon Transcribe audio to improve accuracy. Opt-out available through service policy settings.
Microsoft — Acknowledged human review of Cortana and Skype audio. For Azure Speech Services, Microsoft states customer content is not used for improvement without explicit consent.
Apple — Admitted to human review of Siri recordings in 2019. Now requires explicit opt-in for sharing audio with Apple for improvement.

Encryption

Google — TLS in transit. AES-256 at rest for stored data. Customer-managed encryption keys (CMEK) available for enterprise customers.
Amazon — TLS in transit. AES-256 at rest. AWS Key Management Service (KMS) integration for customer-managed keys.
Microsoft — TLS in transit. AES-256 at rest. Azure Key Vault for customer-managed keys. Option for double encryption.
Apple — TLS in transit. On-device data protected by device encryption. Cloud-processed audio encrypted but Apple holds the keys.

GDPR Compliance

Google — Offers Data Processing Agreement. EU data residency options available. Reliance on Standard Contractual Clauses for EU-US transfers. Complicated by Schrems II ruling.
Amazon — Offers GDPR Data Processing Addendum. EU region processing available. Standard Contractual Clauses for international transfers.
Microsoft — Offers Data Protection Addendum. EU Data Boundary initiative to keep EU data within EU. Most advanced EU compliance posture among US providers.
Apple — Emphasizes privacy as a core value. Processes some data on-device which avoids transfer issues. Cloud-processed data subject to Apple's privacy policy. Less enterprise-focused compliance tooling.

Opt-Out Mechanisms

Google — Data logging can be disabled per API request. Requires developer implementation. End users typically have no direct control.
Amazon — AWS AI Service Opt-Out Policy allows opting out of data use for service improvement. Must be configured at the organization or account level.
Microsoft — Granular controls available through Azure portal. Connected containers offer more control. Custom Speech data can be deleted.
Apple — Users can opt out of Siri and Dictation data sharing in device Settings. On-device processing available for some languages eliminates cloud transmission.

Key Findings from the Comparison

No Provider Offers True Zero-Knowledge Processing

Despite marketing claims about privacy and security, every cloud provider processes your audio on servers they control. Even with encryption, opt-outs, and data processing agreements, your voice data exists on third-party infrastructure for at least the duration of processing. This creates an irreducible privacy risk that no policy can fully mitigate.

Opt-Out Is Not the Default

Across all four providers, the privacy-protective settings require explicit action. Data logging, human review participation, and model training contributions are typically enabled by default. Users and developers who do not actively configure opt-out settings are contributing their voice data to these companies' improvement pipelines.

Human Review Exists Everywhere

Every major cloud speech provider has acknowledged some form of human review of audio recordings. While controls have tightened following public backlash, the practice has not been eliminated. If your audio is processed on a cloud server, there is a non-zero probability that a human will listen to it.

GDPR Compliance Is Complex and Uncertain

For EU-based organizations, using any US-based cloud speech service involves navigating a complex web of data processing agreements, standard contractual clauses, and legal uncertainty created by the Schrems II ruling. Full compliance requires significant legal and technical effort, and the regulatory landscape continues to shift.

Enterprise Features Come at Enterprise Prices

The strongest privacy protections — customer-managed encryption keys, VPC endpoints, on-premises containers, EU data residency — are typically available only on premium enterprise tiers. Small businesses and individual users often lack access to these safeguards.

The Pattern Is Clear: Cloud Architecture Is the Problem

The comparison reveals that while individual policies vary, the underlying issue is the same across all providers: the cloud-based architecture itself is the privacy problem. As long as audio leaves your device, you are accepting some level of risk regarding data exposure, retention, human review, and regulatory compliance.

The differences between providers are marginal compared to the fundamental difference between cloud processing and local processing. Whether Google retains your audio for 30 days or 6 months matters less than whether your audio leaves your device at all.

The Zero-Data Alternative: Local Speech Recognition

Modern local speech recognition eliminates every privacy concern identified in this comparison. When audio is processed entirely on your device:

There is no data transmission to intercept or subpoena.
There is no server-side retention or logging.
There is no human review of your recordings.
There are no GDPR data transfer issues to navigate.
There is no dependency on a third party's privacy policy.

Scrybapp embodies this approach. Running OpenAI's Whisper model entirely on your Mac, it provides speech-to-text that is completely private by architecture, not just by policy. No audio data ever leaves your device — not for processing, not for improvement, not for any reason.

Learn more about how Scrybapp protects your voice data.

When Does Cloud STT Still Make Sense?

Despite the privacy concerns, cloud speech-to-text still has legitimate use cases:

Batch processing of non-sensitive audio — Processing large volumes of public audio content (podcasts, public meetings) where privacy is not a concern.
Custom vocabulary at scale — Some cloud services offer custom model training that can improve accuracy for specialized domains.
Server-side applications — Applications where audio originates on a server (like phone call transcription) and already exists in a cloud environment.
Devices without local processing power — Low-power IoT devices that cannot run speech models locally.

For individual desktop use, however — dictating emails, writing documents, coding, taking notes — local processing is strictly superior on both privacy and convenience grounds.

Making the Switch to Private Speech-to-Text

If you are currently using a cloud-based speech-to-text service and want to transition to a private, local alternative, the process is straightforward:

For Mac users — Download Scrybapp and start dictating immediately. It works in every application and supports 99+ languages.
For multilingual needs — Scrybapp auto-detects your language and can even translate your speech in real-time from one language to another.
For team deployments — Since Scrybapp runs entirely on-device with a one-time license, there are no per-user monthly costs and no data governance concerns.

Conclusion: Privacy Requires Architecture, Not Just Policy

Comparing the privacy policies of Google, Amazon, Microsoft, and Apple reveals that while some providers are better than others, none can offer the privacy guarantees that come from simply keeping your audio on your device. Policies change, breaches happen, and legal frameworks shift. Architecture is permanent.

For a deeper dive into how cloud speech recognition works at a technical level and why local alternatives are gaining momentum, read our article on how cloud-based speech recognition works. And to understand the specific risks of Google's service, see our Google Cloud STT privacy analysis.