Multi-speaker
dialogue text extractor.
Pull clean dialogue out of a multi-speaker recording — attributed by speaker, sequenced by timeline, ready for editorial. No more 'who said what' guesswork in the dailies.
- Free up to 60 min
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- 100% word accuracy
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- Speaker labels included
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- 99+ languages
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Drag & Drop
MP3, MP4, M4A, MOV, AAC, WAV, OGG, OPUS, MPEG, WMA, WMV
Dialogue Extraction Pipeline
Watch the exact pipeline that runs when you upload media to Pxlify.
Upload & Extract
explainer_video.mp4
Whisper Speech AI
Converting audio to words...
Studio Transcripts
Synced SRT & VTT Exports
explainer_video.mp4
Extracting high fidelity audio streams...
Extract attributed dialogue from any recording
Speaker labels. Frame-accurate timestamps. Editorial-friendly exports.
Timed Highlights
Aligns audio signals with precise segment timestamps, ensuring transcripts fit video timelines perfectly.
Whisper Speech Model
Leverages neural transcription frameworks to capture speech patterns, technical terms, and complex vocabulary.
Multi-Format Exports
Export to SRT, WebVTT, Advanced SSA (.ass), JSON, Word (.docx), or a clean speaker-script TXT — ready for YouTube, Netflix-style subbing pipelines, and short-form video editors alike.
Interactive Playback
Click any word or timestamp in the transcript to jump the video directly to that spoken segment.
Privacy Secured
Local preprocessing allows you to play and test files locally in the browser sandbox before uploads are triggered.
Inline Studio Editor
Refine and update text segments directly on the dashboard with instantaneous state synchronization.
Extract dialogue in 3 steps
Upload, name speakers, export.
Upload your video
Drag in a local file (.mp4, .webm, .mov) or pick an existing recording from your library.
Auto-generate timestamps
Pxlify analyzes the audio, splits it into speech segments, and timestamps every line automatically.
Refine & export
Search segments, edit lines inline, sync playback timings, then export to SRT, VTT, ASS, JSON, DOCX, or speaker-script TXT.
Dialogue extractor FAQs
Interview rigs, panel mics, rehearsal cams, podcast capture, and field-mixer outputs — anything with discernible per-speaker audio.
Yes — millisecond accuracy, with snap-to-speech-boundary segmentation.
Cleaner audio works best, but the underlying model is robust to typical field noise (HVAC hum, distant traffic, room tone).
DOCX, TXT, SRT, VTT, ASS, JSON. JSON includes word-level data for editorial NLE imports.