Filewisp

Amazon Transcribe JSON to SRT & VTT

Convert Amazon Transcribe JSON results into SRT, WebVTT, or TXT using item timestamps and speaker labels.

Checks before and after data conversion

1Before converting

  • Keep the source file and confirm its encoding and data format.
  • Check whether the first row contains headers and whether field names look correct.
  • For personal or sensitive data, confirm where processing happens and who will receive the output.

2After converting

  • Use the preview to verify text, column names, and row counts.
  • Open the result in Excel or the destination system and check dates and long numbers.
  • Save the converted file under a new name so it can be compared with the source.

Common next steps

What is Transcribe JSON to Subtitles?

Group pronunciation and punctuation items, or audio_segments, into timed subtitle cues. This is useful for existing JSON and jobs that did not request subtitle output.

Turn word timestamps into readable cues

Words are grouped by punctuation, character count, duration, and speaker changes so cues do not become excessively long. Speaker labels are prefixed as [spk_0] when available.

SRT is widely used by video editors, VTT fits web video captions, and TXT provides the transcript without timecodes.

Transcribe fields used

  • start_time and end_time from results.items
  • pronunciation and punctuation
  • speaker_labels
  • results.audio_segments
  • Full text from results.transcripts

Choose a subtitle format

SRT
A common subtitle format for video editors and hosting platforms.
VTT
Designed for WebVTT players and HTML video captions.
TXT
Transcript text without subtitle timecodes.

How to use

  1. 1Choose an Amazon Transcribe JSON result
  2. 2Click convert
  3. 3Review cues and speaker labels
  4. 4Download SRT, VTT, or TXT

FAQ

Can Amazon Transcribe output SRT directly?

Current jobs can request subtitles. This tool is useful for existing JSON or jobs created without subtitle output.

Are speaker labels preserved?

Yes. Labels from speaker_labels or individual items are added to cues.

Does it work with Japanese transcripts?

Yes. Japanese punctuation is recognized and unnecessary spaces between CJK characters are avoided.

Related tools for the next step

Need help choosing the right workflow?

The guide section covers format differences, compression tips, and common PDF workflows.

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