Free Audio & Video to Text — Private Whisper AI
Transcribe meetings, lectures, podcasts, and Zoom recordings with OpenAI's Whisper AI — running entirely in your browser. Works for MP3, WAV, MP4, and video files up to 150 minutes. Your recordings never leave your device. Export as plain text, SRT subtitles, Markdown, or structured JSON.
100% private — your audio never leaves your device.
The Whisper AI model runs entirely in your browser. Zero server uploads.
All 99 Whisper-supported languages available — type to search by name or code (e.g. Thai, th). Auto-detect works well for most audio; set manually if detection is wrong.
Drag & drop audio or video, or click to browse
MP3 · WAV · M4A · MP4 · WebM · up to 150 min
Paragraph breaks are inserted at natural pauses (>1.5s) to aid readability — not true speaker diarization.
How it works
Drop your file
Drag any MP3, WAV, M4A, MP4, or WebM file (audio or video, up to 150 min). It stays in your browser — zero uploads.
Whisper AI transcribes locally
The model runs in a Web Worker via WebGPU or WASM. First run downloads the model (~75 MB for Base); later runs are instant.
Export to your format
Jump through the transcript with the audio player, then download TXT, SRT subtitles, Markdown for Notion, or JSON.
How the Audio Transcriber Works — Technical Details
SimpleTool uses OpenAI Whisper models (distributed as ONNX via the Hugging Face CDN) executed with Transformers.js v4 inside a browser Web Worker. The model runs via WebGPU on supported hardware with an automatic WebAssembly (WASM) fallback for CPU-only devices. No server connection is opened during transcription — only the one-time model download.
Audio files are decoded via the browser's native Web Audio API and resampled to 16 kHz mono Float32 using OfflineAudioContext— the exact format Whisper was trained on. Long recordings are processed in 30-second chunks with 5-second overlap to preserve context across boundaries. Audio extracted from video containers (MP4, WebM, MOV) is handled by the same pipeline.
Paragraph breaks are inferred from natural pauses (silence gaps >1.5 seconds) to aid readability. This approximates speaker turns for meeting audio but is not true speaker diarization. Word-level timestamps are preserved in the JSON export for downstream tooling.
When do you need browser-based audio or video transcription?
Real situations where running Whisper locally beats AI transcription services, professional transcription services, or any cloud transcription service.
Confidential meeting transcripts
Internal board meetings, M&A calls, performance reviews, legal depositions — the exact recordings that should never sit in a third-party SaaS's cloud, even briefly. Local transcription produces the transcript without the recording leaving your device.
Zoom / Teams / Meet recordings
You recorded a 60-minute call locally to MP4 or M4A. Whisper transcribes it in your browser; you get a searchable transcript with timestamps + an SRT subtitle file for the video archive. No re-upload to a transcription service.
Lecture & class transcripts
Students recording lectures on a phone or laptop. Whisper transcribes the audio file in the browser to a searchable transcript for study, with timestamps to jump back to specific moments. No university policy violation from uploading copyrighted lecture content.
Podcast show notes
Podcasters generating show notes, timestamped chapter markers, and pull-quotes from each episode. The Markdown export includes timestamps directly compatible with most podcast publishing platforms. No subscription, no token cost.
YouTube video subtitle generation
Creators generating SRT subtitle files for their own videos before upload. The SRT export drops directly into YouTube Studio, Premiere Pro, or any editor that reads subtitles. Same workflow for TikTok, Reels, Shorts.
Journalist interview transcripts
Reporters transcribing source interviews — especially sensitive sources where the audio cannot legally or ethically be uploaded to a SaaS. Local Whisper preserves source confidentiality while producing the transcript needed for quote attribution.
Voicemail batch transcription
Small business owners or solo professionals batch-transcribing accumulated voicemail files (.m4a from phone exports). One transcript per voicemail, searchable for callbacks, with timestamps to verify exact wording on important messages.
Voice memo to text
Field notes recorded on a phone as voice memos. Transcribe to text in the browser without uploading personal voice recordings to a cloud-based "voice memo to text" service. The output drops into Notion, Obsidian, or any note-taking tool.
How SimpleTool Compares
Five common transcription routes. Different price, different privacy posture, different output quality.
| Feature | SimpleTool | AI Transcription Service | Professional Service | Podcast/Video Editor |
|---|---|---|---|---|
| Cost | Free | Free tier limited; paid plans | Per-minute paid | Subscription |
| Files stay private (no upload) | Yes | No — uploaded + retained | No — uploaded + human-reviewed | No — uploaded to cloud |
| Engine | OpenAI Whisper (local) | Proprietary cloud ASR | Mix of AI + human | Proprietary cloud ASR |
| Account required | No | Yes | Yes | Yes |
| Multi-language (auto-detect) | Yes (Whisper) | Limited free | Paid feature | Paid feature |
| Speaker identification | Paragraph breaks (silence-based) | Yes (paid) | Yes | Yes |
| SRT subtitle export | Yes | Paid | Yes | Yes |
| Word-level timestamps in export | Yes (JSON) | Limited | Yes | Yes |
| File size / length limit | Browser RAM (~150 min) | Free tier caps | No cap (paid per minute) | Subscription caps |
| Source / data policy | Client-side, no logs | Files stored on servers | Files reviewed by humans | Files stored on servers |
For long-form (multi-hour) recordings or true multi-speaker diarization, dedicated services (professional transcription services and audio/video editing platforms) have an accuracy edge — they layer post-processing on top of the same Whisper-class models. SimpleTool wins when (a) the recording is sensitive and shouldn't leave your device, (b) you don't want to pay per minute or subscribe, or (c) the silence-based paragraph breaks are good enough for the use case.
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