Podcast and video chapter prep
Transcript Timestamp Extractor
Extract MM:SS and HH:MM:SS markers with their surrounding labels from transcripts, show notes, or editing notes.
Timestamped text
Text is processed locally.
Timestamp list
Run the tool to create output.
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Continue the audio workflow
Move between raw audio, timed subtitle files, and publishable text without returning to the home page.
What does Timestamp extractor do?
Extract existing MM:SS or HH:MM:SS timestamps and their surrounding labels from transcript text. SceneDub preserves source order and removes exact duplicate entries. It does not listen to audio, identify topics, or invent chapter titles.
- Input
- Text containing timestamps and optional labels
- Output
- Tab-separated timestamps and text
- Processing
- Local text extraction
A practical workflow
- Paste text that already contains time references.
- Extract timestamps and inspect their labels and order.
- Edit the list for your destination's chapter rules before publishing.
Capability notes updated . Editorial methodology
From recording notes to a timestamp list
Input / starting point
00:00 Introduction
01:30 Microphone setup
03:15 Recording a takeOutput / result
0:00 Introduction
1:30 Microphone setup
3:15 Recording a takeThe output is an editing aid. For YouTube chapters, verify a 00:00 start, at least three ascending timestamps, and chapters lasting at least 10 seconds.
Best for
- Pulling podcast chapter markers from notes
- Cleaning YouTube chapter drafts
- Collecting edit timecodes from transcripts
- Turning timestamped notes into a compact list
Key features
- MM:SS recognition
- HH:MM:SS recognition
- Label preservation
- Duplicate removal
- Chronological second values
Limits to know
- The source text must already contain timestamps
- Frame-based SMPTE timecode is not parsed
- The tool preserves source order rather than re-sorting
- Review ambiguous numeric text before publishing
Practical guides
Need sample files? The free creator kit includes caption templates, transcript examples, and original voice-practice scripts.
Remove Timestamps From a Transcript Without Rewriting It
Turn timestamped dialogue into readable paragraphs, preserve attribution when needed, and understand what deterministic transcript cleanup changes.
Turn Transcript Timestamps Into YouTube Chapter Notes
Extract timestamped labels, organize meaningful chapter boundaries, and check YouTube's chapter requirements before publishing your video description.
Format and platform references
Frequently asked questions
Which timestamp formats are recognized?
The extractor recognizes MM:SS and HH:MM:SS patterns, including timestamps inside common brackets.
Does it generate timestamps from audio?
No. It extracts markers already present in text. Use transcription when you need timing generated from media.
Are repeated timestamps removed?
Exact repeats with the same timestamp and label are included once.
Can I use the list for podcast chapters?
Yes. The output keeps a normalized timestamp followed by the label found on that source line.