99 languages
speech-to-text.
Upload audio or video in any of 99 supported languages and Pxlify returns a timestamped, diarized transcript — no manual language picker needed, auto-detect is on by default.
- Free up to 60 min
- ·
- 100% word accuracy
- ·
- Speaker labels included
- ·
- 99+ languages
- ·
Drag & Drop
MP3, MP4, M4A, MOV, AAC, WAV, OGG, OPUS, MPEG, WMA, WMV
99-Language STT 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...
Speech-to-text across 99 languages
Auto-detect. Per-language quality tuning. Diarized output.
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.
Transcribe in any of 99 languages in 3 steps
Upload, auto-detect, 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.
99 languages FAQs
No. Auto-detect runs by default; you can override if the recording is multilingual.
No system is perfectly even, but Pxlify's underlying model performs strongly on the major world languages and well on long-tail languages too.
Yes — bilingual passages are handled by chunked detection, though edge cases benefit from a manual source-language pick.
Yes. Diarization is language-agnostic and works across the full 99.