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Before sending a recording to a cloud transcription API, check what happens to the audio, transcript, and request data separately. The answer can change with the provider, endpoint, account settings, storage destination, and contract. Use the checklist below to reduce what you send, verify the controls that apply to your exact API path, and protect the transcript after it comes back.

What happens to audio and transcripts after submission?

There is no single retention or privacy rule for cloud transcription. A provider may handle input audio, returned text, abuse-monitoring logs, and application state differently. Training use is also a separate question from retention: content excluded from model training may still be processed or logged to operate and secure a service.

These distinctions are documented for specific services, not as a universal comparison of equivalent configurations:

Service documentation What it says about use or retention Important boundary
OpenAI API data controls API inputs and outputs are not used to train models by default. Default abuse-monitoring logs may be retained for up to 30 days. The 30-day period concerns abuse-monitoring logs; do not treat it as a statement that every audio or transcript copy has the same lifetime.
Google Cloud Speech-to-Text data usage FAQ For synchronous and streaming requests, audio is processed in memory without customer data storage. Asynchronous transcripts are stored for approximately five days so customers can retrieve them. Content from customers not opted into data logging is used only to provide the service. These handling details differ by request mode. Google also offers a separate opt-in data-logging program.
AWS Transcribe encryption documentation AWS documents TLS 1.2 for data in transit and encryption options for transcription outputs. Those encryption details do not establish how long audio or results are retained; the relevant output destination and its settings matter.

Google Cloud’s Speech-to-Text data usage FAQ states: “Google does not claim any ownership in any of the content (including the audio data and returned transcript) that you transmit to the Cloud Speech-to-Text API.” Ownership language does not, by itself, answer questions about processing, storage, access, or deletion.

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Before upload: verify the service and minimize the recording

  1. Send only the audio needed

    Trim unrelated conversation and avoid including identifiers or sensitive passages that are not needed for the transcription task. This is a general data-minimization practice, not a provider setting. If the recording contains material you do not have a reason or authority to disclose, do not assume that transcription makes the disclosure harmless.

  2. Pin down the exact API path

    Record the provider, product, endpoint, request mode, account or project, and output destination. For example, distinguish synchronous, streaming, and asynchronous Speech-to-Text requests. A retention statement for one mode should not be applied to another, nor should a setting for one product be assumed to cover a different API.

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  3. Read data-use and retention terms as separate questions

    Check whether submitted content is used for model training or service improvement, whether that treatment is a default or an opt-in, what abuse-monitoring or operational logs may contain, and how long each audio, transcript, and application-state copy persists. For the OpenAI API, inputs and outputs are excluded from training by default, while default abuse-monitoring logs may be retained for up to 30 days. Those are distinct statements, not a blanket retention period for every copy.

  4. Check optional data logging and its deletion path

    Find out whether a data-logging program is enabled, whether enabling it permits service-improvement use, and what happens to logged material when you delete a project or account. Google Cloud documents an opt-in Speech-to-Text data-logging program that permits use of logged data to improve service quality. Google says deleting the project does not delete data already logged through the program; a separate deletion request is required.

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  5. Verify geography for processing, storage, and system data

    Do not treat “regional” as a complete description. Google Cloud says processing is global by default and describes EU and US multi-region endpoints to limit processing to those geographies. OpenAI’s data-residency documentation distinguishes regional storage from processing, notes that system data may be outside the selected region, and describes additional requirements for non-US regions. Confirm the endpoint and account eligibility for your use case, and check where the resulting transcript and your own logs will be stored.

During the request: secure the connection and credentials

  • Use authenticated, encrypted connections. AWS documents TLS 1.2 in transit for Transcribe. This protects data in transit on the documented path; it does not settle retention or security of the output after delivery.
  • Keep API credentials out of recordings and client-side code. Store keys in an appropriate secrets mechanism, restrict who can use them, and rotate or revoke credentials when exposure is suspected.
  • Limit request logging in your application. Logs can accidentally capture request bodies, file names, identifiers, or returned transcripts. Configure logging so it records only what operations require, and restrict access to those logs.

After transcription: protect the returned text and copies

A transcript can preserve names, account details, health information, or confidential discussion from the recording. Treat the text as sensitive source material, not as harmless simply because it is no longer audio.

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  1. Choose whether to retain the transcript

    If the application does not need a durable copy, avoid saving one unnecessarily. If it does, identify the storage destination and apply access controls and encryption appropriate to the content. Google Cloud documents encryption at rest by default and customer-managed encryption keys through Cloud KMS for supported resources; verify that the specific resource used in your flow is covered.

  2. Set a deletion schedule for every customer-controlled copy

    Account for transcripts, uploaded source files, temporary files, application logs, exported files, and backups. Define who can access each copy and when it is removed. Deleting a local source file does not establish that a provider-side or downstream copy has been deleted.

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  3. Confirm deletion with the party that controls the copy

    Identify the deletion mechanism for provider-held content, optional logged data, and your own storage separately. A project deletion may not erase data retained through an optional logging program, and a cloud transcription API cannot delete copies your application has written elsewhere.

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When to require a contract or specialist review

For regulated, contractual, or otherwise high-risk recordings, product documentation alone may not resolve your obligations. Before deployment, confirm the applicable agreement, jurisdiction-specific requirements, support-access terms, subprocessors, deletion route, and eligibility for the selected endpoint with the provider and appropriate counsel. Do not infer that a particular endpoint or encryption setting eliminates provider access, all logging, or legal retention.

Pre-upload checklist

  • Have a valid reason and authority to send this recording to the selected service.
  • Remove unrelated audio and identifiers where practical.
  • Identify the provider, product, endpoint, request mode, account, and output destination.
  • Check training use, service-improvement use, abuse-monitoring logs, transcript storage, and application-state retention separately.
  • Verify optional data-logging settings and the deletion process for logged data.
  • Confirm processing geography, storage geography, and any account or endpoint eligibility requirements.
  • Secure credentials and connections, and prevent sensitive payloads from entering unnecessary logs.
  • Set access controls and a deletion schedule for transcripts, source files, logs, and backups.

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