Step 1 for Meeting: Download your meeting recording
From Zoom cloud, local storage, Google Meet, or Teams. File formats: MP4, MOV, WebM.
VideoText workflow guide
Convert meeting into searchable transcript output with speaker labels, timestamps, and export-ready subtitle files from the same workflow.
From Zoom cloud, local storage, Google Meet, or Teams. File formats: MP4, MOV, WebM.
Upload takes 30-60 seconds for typical 30-60 min meetings.
Transcript with timestamps ready in 2-5 minutes. Optional: AI-generated action items and key decisions. The result stays organized for meeting recordings, captions, summaries, and searchable transcript exports.
Email the transcript, share a read-only link, or export to Slack/Notion.
Use the summary to identify next steps. Copy/paste into project management tool.
Full time-coded transcript with consistent speaker diarization labels, paragraph breaks at topic transitions, and timestamps formatted per the target style guide. Suitable for DOCX delivery, editorial review, or agency handoff.
Subtitle files generated from the same transcription job, so timing alignment between transcript text and caption files is guaranteed. No separate captioning tool required, no risk of timing drift between transcript and subtitle outputs.
Structured summary and auto-detected chapter timestamps for long-form content. Chapters are formatted for paste-ready YouTube description insertion. Summary is formatted as a structured brief suitable for show notes, team handoffs, or newsletter conversion.
No more hours typing notes. Upload the recording, get transcript + summary in 5 minutes. Share with team. Use the meeting transcript as the source of truth for editing, publishing, and handoff.
Can't make a live meeting? Search the transcript later. Find the exact moment a decision was made.
Meeting recordings transcribed and stored for compliance, legal, or quality assurance purposes.
Meeting transcript of customer meetings = direct customer voice. Search for specific feature requests or pain points.
When two speakers overlap for more than 2 seconds, diarization models frequently misattribute the trailing portion of the overlap to the wrong speaker. In interview transcripts, this produces a block of content assigned to the guest that should belong to the host — or vice versa. Manual review is required to correct this.
Zoom recordings with network instability produce audio dropout gaps — typically 0.5–3 seconds of silence or garbled audio. Transcription of these sections produces either a gap in the text or a run of plausible-sounding but incorrect words. Sections with network dropout require manual review against the audio.
Transcription engines that split audio into 30-minute chunks for processing introduce artifacts at chunk boundaries: the last sentence of chunk 1 and the first sentence of chunk 2 may both contain the same words, or a sentence may be split at an unnatural word boundary. Reviewing segment transitions is part of long-file QA.
Medical, legal, financial, and engineering terminology is consistently misrecognized by general-purpose ASR models. "Tachycardia" becomes "taxi cardia." "EBITDA" becomes "e bit duh." These require a domain-specific post-edit pass — a transcript correction process that benefits from knowing the technical vocabulary in advance.
DOCX preserves paragraph structure and allows tracked-changes editing for collaborative review. PDF locks the formatting for delivery but cannot be edited without re-conversion. For client review workflows, DOCX is the correct delivery format; PDF is for final archiving after all revisions are complete.
SRT uses comma separators in timestamps: 00:01:23,456 → 00:01:25,123. VTT uses period separators: 00:01:23.456 → 00:01:25.123. Swapping the separator character causes parsing failures. SRT does not support styling metadata; VTT supports positioning, color, and timing cues.
Per-speaker-turn timestamps are useful for review and quotation but create dense formatting that reduces readability. Fixed-interval timestamps (every 2 minutes) are readable but make it harder to find a specific speaker moment. Most academic and journalistic workflows prefer per-speaker-turn; legal and court transcription typically requires fixed-interval.
JSON output includes segment start/end times, speaker labels, confidence scores, and text — structured for import into search platforms, CMS systems, and custom workflows. Per-segment confidence scores identify sections likely to require manual review.
Upload your video or audio file. Click Transcribe and get a full transcript in seconds. Export as SRT, TXT.
Use a short real recording first, then compare transcript structure, speaker labels, subtitles, and cleanup time before moving longer files through the same workflow.
TXT, SRT, VTT. Paid plans add JSON, CSV.