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Open — Transparency report

Real numbers, real data

We publish our processing stats, accuracy benchmarks, and technology choices publicly. These are numbers we measured — not marketing claims. Updated monthly.

These figures are VideoText’s own operations. For third-party industry statistics on captions, hearing loss, and speech recognition, see transcription statistics.

Last updated: March 14, 2026

At a glance

127,000+
Videos transcribed
Cumulative since launch (January 2026)
42,000+
Hours of audio processed
Equivalent to 4.8 years of continuous audio
~1.5 min/hr
Median processing time
Per hour of source video, under normal load
57
Languages supported
Transcription (Whisper) + 50+ translation targets
0
Files stored after processing
Every file deleted immediately after job completes
98.5%
Word accuracy (clean audio)
Whisper large-v3 on clear speech, measured internally

Accuracy by audio condition

Measured on our test set of 200 clips (total ~18 hours). Word Error Rate converted to accuracy percentage. Test conducted with Whisper large-v3, March 2026.

Audio condition
Word accuracy
Studio-quality audio, native English speaker99.1%
Standard laptop microphone, quiet room98.2%
Zoom recording, 2 speakers97.4%
Phone audio, light background noise95.8%
Non-English content (manually set language)96.2%
Non-English content (auto-detect)93.1%
Heavy background music or noise87.4%

* These are real internal benchmarks, not vendor-reported figures. Whisper performance varies by language, audio quality, and content type.

Processing speed

Measured from upload-complete to transcript-complete. P50 = median; P90 = 90th percentile (worst typical case). Paid plans have queue priority during load.

Video length
P50 (median)
P90
5 min video~25 sec~55 sec
15 min video~1.2 min~2.5 min
30 min video~2.5 min~4.5 min
60 min video~5 min~8 min
2 hour video~10 min~16 min

Technology stack

We publish our stack so you know exactly what processes your content. No black boxes.

Transcription modelOpenAI Whisper large-v3 (self-hosted)
Audio extractionFFmpeg — mono WAV, 16kHz, before Whisper
TranslationLLM-based translation preserving timestamp structure
Video compressionFFmpeg CRF-based H.264 encoding
Subtitle burningFFmpeg libass filter with custom font rendering
Queue systemBull (Redis-backed) with plan-based priority weights
StreamingServer-Sent Events — results stream as segments complete
FrontendReact + Vite, TypeScript
BackendNode.js, Express
PaymentsStripe

Our data commitment

  • ✓Files are deleted from our servers immediately after processing completes.
  • ✓We store job metadata (duration, tool type, plan) for billing — not content.
  • ✓We do not sell your data to any third party.
  • ✓We do not use your content for training AI models.
  • ✓We do not store transcripts or subtitle files server-side.
  • ✓All transit is encrypted via HTTPS.

How we compare

Most transcription tools don't publish accuracy benchmarks or processing speeds publicly. We do, because we think you should know what you're buying before you commit.

Benchmark hub links