Source-first translation with copy and TXT export
Use this audio translator to turn recorded speech into translated text you can inspect beside the source transcript. Upload, record, or import supported media, create the source-language text first, choose a target language, and translate through the existing paid AI action. The output can be copied or exported as TXT; it is not dubbed audio or cloned speech.
First create the source transcript, then choose a target language. Output is translated text, not dubbed audio.
Choose one file to continue in the transcription workspace.
Workflow
Upload a recording, record in the browser, or import supported public media. Choose the spoken language when you know it. The first result is a source-language transcript with timestamps, giving you something concrete to correct before translation.
Correct proper nouns, numbers, product names, legal wording, and passages affected by overlap or noise. Translation cannot reliably fix an error already present in the source transcript, so this checkpoint protects the next step.
Use the existing Translate action on the completed task, inspect the credit estimate, select the target language, and create translated text you can copy or export as TXT. Keep both versions available so a bilingual reviewer can trace important wording back to the source.
Decision guide
Transcription represents speech in its source language. Translation expresses that text in a different language. Because they are separate operations, correcting the source transcript before translating can prevent a recognition mistake from being carried into every target sentence.
This page produces text that can be read, copied, or exported as TXT. It does not synthesize a target-language voice, imitate the speaker, lip-sync a video, or interpret a live call. Choose a dubbing product if audio replacement is the actual deliverable.
Medical, legal, financial, safety, immigration, employment, and contractual content can carry serious consequences. Use a qualified human translator or subject expert, preserve the recording, and verify key terms rather than treating generated text as final authority.
Multiple speakers, code-switching, dialect, cross-talk, and poor microphones affect the source transcript before translation begins. Speaker labels can organize voices, but they do not identify real people and they do not replace contextual review.
Use cases
Keep the original transcript with timestamps, correct names and quotations, then create a target-language reading copy for a bilingual editor.
Turn authorized field recordings into searchable source text and a working translation while preserving passages that require specialist interpretation.
Translate a checked transcript, then adapt timing, line length, reading speed, tone, and on-screen context in a dedicated caption or video editor.
Generate a working text translation for orientation, while sending material decisions, commitments, and technical statements to a qualified reviewer.
Commercial comparison
Comparison checked 2026-08-13. Use the linked sources to verify live terms.
| Decision factor | Whisper AI | Notta | Flixier |
|---|---|---|---|
| Core output | Translated text retained with the source transcript, plus copy and TXT export | Transcription and translation inside a broader notes workspace | Transcript/subtitle translation with optional creative voice workflows |
| Source-first checking | Source transcript is completed and can be corrected before the Translate action | Check its current editor and translation workflow for source retention | Timeline and subtitle workflow supports visual editing context |
| Voice dubbing | Not provided; output is translated text | Check the active product for current voice features | Positions optional voice generation as part of its broader workflow |
| Best fit | People who want a traceable transcript-to-translated-text path | Teams comparing translation inside a meeting-notes product | Video creators who also need timeline, subtitle, or voice production tools |
Choose Whisper AI when the deliverable is reviewable translated text with TXT export and source traceability matters more than synthetic voice production. Choose a broader video editor when dubbing and timeline work are essential, then verify its live pricing and language support.
Before you begin
Clear answers
No. It creates translated text you can copy or export as TXT from a completed source transcript. It does not dub the recording, clone the original speaker, or generate real-time interpreted audio.
The source text exposes recognition mistakes before they become translation mistakes. It also gives reviewers timestamps and original wording for checking names, numbers, terminology, and nuance.
No. Transcription minutes and the paid AI translation action are distinct. The completed workspace shows the existing credit estimate before translation is submitted.
You can enable speaker separation during transcription, but generated labels represent detected voice groups rather than verified identities. Correct the source and attribution before relying on translated dialogue.
Generated translation can support orientation, but it should not be the sole authority for high-stakes decisions. Use a qualified human translator or subject expert and verify against the recording.
Evidence
Product and competitor details were checked on 13 August 2026. Commercial pages can change, so follow each source before making a purchase or uploading sensitive media. Comparisons describe the checked pages and do not imply an endorsement.
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