1. Load Audio or Video Track
Drop any audio or video recording into the local workspace. Audio decoding executes in-memory without uploading bytes to external servers.
Transcribe spoken speech and audio to text in your browser using local Whisper AI. Generate word-level subtitle cues, edit dead air with sentence protection, and export WebVTT or SRT files.
Ready for a local audio or video file
Reading media and computing RMS energy…
Balanced (~-38dB): Calibrated natural balance recommended for podcasts, YouTube videos, and dialogue.
Automatically removes silence before first speech and after last speech.
00:14.2 → 00:16.8 (2.6s gap)
1.6s quiet gap; keeps 0.32s breathing room.
0 silences found (0.0s dead air) · 0 will be cut, 0 kept
Removes 80Hz rumble, 50/60Hz hum, room hiss & mouth clicks
Fills shortened silence gaps with authentic room tone synthesized from your recording, eliminating unnatural "vacuum dropouts".
Protect Intentional Sentences & Pauses
Importing your subtitle transcript locks dialogue boundaries so dramatic reflections and deliberate speech pauses inside sentences are never auto-cut.
Removes verbal hesitation sounds (um, uh, er, like) and repeated stutters.
Total Proposals
0
Active Cuts
0
Restored Pauses
0
Protected Lines
0
Structural Export Validation:
Verified Export Options:
Multi-band spectral Wiener filtering & room rumble removal
Lossless 16-Bit Master Audio & Edit Ledger Export
Rendered locally in browser memory with 8ms anti-click micro-fades. Zero server upload.
Timeline files reference your media by file name only. Final Cut Pro, DaVinci Resolve or Premiere Pro will ask you to relink the clip to the original file.
100% browser-local processing · No files uploaded to any server
How this tool decodes, analyzes, and masters your dialogue locally with zero cloud latency.
Drop any audio or video recording into the local workspace. Audio decoding executes in-memory without uploading bytes to external servers.
Run quantized Whisper speech recognition directly in browser WebAssembly to generate word-level timestamped subtitle cues.
Review detected filler words and stutters, protect conversational pauses, and export synchronized WebVTT, SRT, or Audacity label tracks.
Explore companion utilities for dialogue cleanup, speech pacing, and mastering.
Sync and export WebVTT and SRT subtitle tracks with automatic cut realignment.
Detect and trim hesitation sounds and stutters with word-level precision.
Edit video and audio timelines directly by selecting transcript tokens.
Explore the acoustic principles, ITU-R loudness standards, and pacing techniques behind this tool.
How text-audio alignment works: importing SRT/VTT files, protecting enclosed pauses within sentences, and exporting synchronized subtitles.
The mathematics of cumulative cue timecode offsetting: recalculating WebVTT/SRT start and end timestamps proportionally across trimmed pause intervals.
How text-based timeline engines map subtitle tokens to video frame boundaries, preserve sentence structures, and export NLE timelines.
Common Questions & Technical Clarifications
To transcribe audio to text online for free: 1. Drop your audio or video file into AutoSilenceCut. 2. Click Transcribe with AI to run browser-local Whisper speech recognition. 3. Review word timestamps and export W3C WebVTT (.vtt) or SubRip (.srt) subtitle files.
No. AutoSilenceCut executes Whisper speech recognition entirely inside your browser using WebAssembly and Web Workers. Your audio recordings, transcripts, and filenames never leave your device.
The built-in browser-local model is optimized for English speech recognition. For other languages or existing transcripts, you can import standard .vtt or .srt subtitle files directly.
Transcribing audio generates word-level timestamps that automatically identify hesitation fillers (um, uh), repeated-word stutters, and bad take retakes, while locking intentional pauses inside spoken sentences.
You can export synchronized WebVTT (.vtt) subtitles, SubRip (.srt) caption files, Audacity cue label tracks (.txt), or RFC-compliant CSV edit ledgers.