SCENEDUB.

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.

One free try, then Google sign-in.

Continue the audio workflow

Move between raw audio, timed subtitle files, and publishable text without returning to the home page.

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

Questions this tool answers

timestamp extractorextract timestamps from transcriptpodcast chapter timestamp toolYouTube timestamp formatterfind timecodes in textchapter marker extractorMM SS extractoronline transcription toolspeech to text onlineaudio to text convertervideo to text convertertranscribe audio to texttranscribe video to texttranscript generatorautomatic transcriptionaudio transcript generatorvideo transcript generatorautomatic subtitle generatorautomatic SRT generatorsubtitle generator onlineSRT generator onlineMP3 to textMP4 to text

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.

Related free tools