Whisper AI Transcribe
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Move from spoken audio to a timed subtitle workflow. Select the spoken language, upload an audio recording, and receive a time-coded SRT subtitle file for editors, podcasters, and accessibility teams.

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Audio-to-SRT conversion built for the task

The workflow is shaped around audio to SRT converter, from an audio recording to a time-coded SRT subtitle file.

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134+ languages for audio-to-SRT conversion

Select the language spoken in an audio recording to guide the transcription process. (audio-to-SRT conversion)

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Speaker labels for audio-to-SRT conversion

Separate voices in multi-speaker material so a time-coded SRT subtitle file is easier to follow and review. (audio-to-SRT conversion)

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A saved workspace for audio-to-SRT conversion

Keep uploaded material and resulting text together so you can return to the audio-to-SRT conversion workflow.

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Protected audio-to-SRT conversion files

Security controls help protect an audio recording while it moves through the transcription workflow. (audio-to-SRT conversion)

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Large-file support for audio-to-SRT conversion

Handle a single upload up to 5GB when the audio-to-SRT conversion task involves longer media.

A good audio to SRT converter workflow should make the next step easier, whether that is review, editing, sharing, or publishing. After transcription, review wording and timing before using the result in an editor, player, or publishing workflow. For editors, podcasters, and accessibility teams, the page emphasizes how to get a time-coded SRT subtitle file and why that output is useful. Its distinct angle is to own the generic audio subtitle format query.