Get a Clean, Readable Transcript
ScreenApp does not have a separate “verbatim” or “non-verbatim” mode to choose between. Upload a recording or record one in the browser, and the transcript that comes back is already close to a clean read: the engine does not reliably keep every “um,” repetition, or false start, so most output reads like a non-verbatim transcript without any extra step.
If you want the transcript tightened further, for example turning a rough section into fully polished prose, AI chat with any recording, so you can ask it to rewrite a passage, remove remaining filler, or condense a section, without leaving the page.
What you get with every recording:
- A transcript with speaker labels and timestamps, in 100+ languages
- A first pass that is already close to clean-read, not a raw word-for-word capture
- transcript corrections, line removal and speaker reassignment saved to the recording
- AI chat on the recording, so you can ask for a cleaner or shorter version of any part
- Export as PDF, DOCX, TXT, SRT and VTT
- Free plan: 2 transcriptions of recordings up to 45 minutes each, with AI chat on both
How to Get a Clean Transcript
- Upload or record: Upload an audio or video file, or record directly in the browser or the mobile app.
- Read the transcript: The transcript, with speaker labels and timestamps, is ready a few minutes after processing finishes. It is already close to a clean read.
- Edit it or ask AI chat for more cleanup: transcript corrections, line removal and speaker reassignment saved to the recording, or AI chat with any recording. Ask it to remove remaining filler from a section, shorten a passage, or rewrite something in plainer language, then export the result.
How close the first pass reads to clean-read depends on the audio: a clear single-speaker recording needs less cleanup than a noisy multi-speaker one. See how we measure accuracy.
Clean Transcript vs Other Apps
| ScreenApp | Rev | GoTranscript | Amberscript | |
|---|---|---|---|---|
| Default style | Close to clean-read by default, no style to pick | Human transcription is clean by default; a verbatim add-on to capture every word, filler, and nonverbal | Clean verbatim or edited, chosen when you order | Clean Read and Verbatim transcription available, on the human service |
| Further cleanup | transcript corrections, line removal and speaker reassignment saved to the recording, or AI chat with any recording | Not stated | AI transcription available, but the page says automated output needs a manual review pass for cleanup | Not stated |
| Turnaround | Minutes | 12 hours or less (human) | 5-day, 3-day, 1-day, or 6 to 12-hour | 5 business days, or 1 business day with a rush order (human) |
| Price | Free plan: 2 transcriptions, up to 45 min each; paid plans from $19/month annual | $1.99/min (human) | Rates behind a linked spreadsheet, not shown on the pricing page | €1.85 (human) |
Sources, checked 2026-09-16: AI chat troubleshooting, Transcript cleaner, ScreenApp pricing, rev.com/pricing, amberscript.com/en/pricing, gotranscript.com/pricing
- vs Rev: Rev’s human transcription is clean by default and offers a verbatim add-on to capture every word, filler, and nonverbal as an add-on when you need every word kept. ScreenApp has one transcription output, already close to clean-read, with AI chat available if you want it tightened further.
- vs GoTranscript: GoTranscript lets you choose clean verbatim or edited when you place an order, and its own page notes that automated output needs a review pass for cleanup. ScreenApp’s transcript needs no separate order or review pass to start close to clean-read.
- vs Amberscript: Amberscript’s human service offers Clean Read and Verbatim transcription available, at €1.85 with a turnaround of 5 business days, or 1 business day with a rush order. ScreenApp’s transcript is ready after processing, with AI chat for any further edits.
Who Needs a Clean Transcript
Meeting and call reviewers want to skim what was said without reading every “um” and restart, so a first pass that already reads clean saves the trim-down step.
Content teams turn interviews and podcast recordings into a script or blog draft, then use AI chat to tighten a passage or cut a tangent before pasting it into an editor.
Students and researchers read back a lecture or interview in text form and ask AI chat to condense a section for their notes.
Customer support teams review call transcripts that already read clearly, without extra time spent removing filler before sharing them internally.
Businesses put meeting transcripts into a shared library where the text is readable on the first pass, not just a raw capture that needs editing before anyone can use it.