Turn video into usable text with a workflow for uploads, language detection, speaker review, captions, long recordings, privacy and transcription jobs.
Video to text turns spoken content in a recording into a transcript that can be searched, captioned and edited. Fish Audio’s workflow accepts an uploaded media file, returns text with language and speaker context where available, and leaves the final review to a person who knows the subject.
It means converting the speech track—not the moving images—into written language. The video editor, the visual demonstration and any on-screen labels still need separate attention. A good transcript captures what was said; a good article also explains what viewers saw.
For pure speech-to-text product information, see the Fish Audio speech to text guide. This page is the media-oriented workflow for people starting with a finished MP4, MOV, WebM or similar file.
If the video is mostly music, gameplay or ambient sound with little speech, clarify what the transcript should capture. The tool produces text from speech; it is not a scene-description system.
Begin with the opening minute, then review the points where the video changes speaker or topic. These are the places where an automatic transcript is most likely to lose context.
Keep a glossary for a series. A recurring name that is corrected once should be reused in every episode rather than corrected from scratch each time.
A transcript is a reading document. Captions are timed fragments designed to appear during playback. They share a source but need different editing rules.
| Output | Primary use | Main requirement |
|---|---|---|
| Full transcript | Search, accessibility, articles | Readable paragraphs |
| Captions | In-player text | Timing and line length |
| Summary | Episode page and promotion | Information hierarchy |
| Content brief | Repurposing | Key claims and quotes |
A timed output depends on the timing fields available in the current product contract. Confirm that support before promising a caption file.
Each uploaded video is planned as a processing job. The job count is more useful than total minutes because product limits and credit charges are applied per request.
| Workload | Jobs | Planning note |
|---|---|---|
| One webinar | 1 | Review names and Q&A speakers |
| Weekly team recording | 4–5 per month | Set retention rules |
| A video course | One per module | Align captions with edits |
| A YouTube archive | One per final video | Batch by title and date |
The $9 Starter pack covers small test batches. Check the current upload limits before estimating a full archive, and keep the source file until the transcript has passed review.
Split at chapter or speaker boundaries and keep a shared identifier for each segment. If the output must be one transcript, join the reviewed segments only after removing duplicated transitions and fixing sentence boundaries.
Do not split in the middle of an important answer just to meet a technical limit. Choose a boundary where the next section can be reviewed independently, and record the source timecode in the job notes.
For a podcast-sized recording, connect to the podcast transcript page. For an API implementation, read speech to text API.
The most common mistake is uploading a draft that differs from the published edit. The transcript then contains sentences viewers cannot find and timestamps that do not align with the final file. Export from the final timeline or clearly label the source version.
The second mistake is treating speaker labels as verified identities. A transcript may know that two voices alternated without knowing which person owns each role. Assign names only after checking the recording, and preserve an “unidentified speaker” label when the evidence is not clear.
Video may contain faces, voices, private documents, customer information or unreleased product footage. Limit upload access, delete source files when they are no longer needed, and keep transcripts in the same secure lifecycle as the original recording.
Record consent for interviews and client work. When the recording is used to clone a voice, read the voice cloning consent guide before creating the voice profile.
A publishable transcript has correct names, clear speaker labels, meaningful punctuation and a short introduction that tells a reader what the video covers. It should not contain visible machine artefacts such as repeated words, broken timestamps in the middle of a sentence or unexplained speaker numbers.
Run a final audio comparison on every quotation that will appear in promotional copy. A transcript can support the edit, but it cannot make an inaccurate claim true.
The upload workflow accepts common audio and video media types, with size limits shown in the current product. Export a clean final file and confirm the format and limit before uploading a long recording.
Timestamp fields depend on the current transcription contract. Verify the available output before planning captions or clip search; a normal transcript may not include word-level timing.
Yes, speakership context can be returned, but review interviews and group calls. Overlapping speech and weak microphones can put a line under the wrong speaker.
Use final edit boundaries or chapters. Keep each job within the current file limit and record the source time range so the edited transcript can be reassembled accurately.
A video transcription is a processing job rather than a per-character generation task. Check the current upload screen for the exact credit cost and limit.