NEW · AI-Powered · 100% Browser-Based

Free Audio Transcription

Transcribe audio and video to text using OpenAI Whisper — running entirely in your browser. No upload, no signup, no time limits. Supports 99 languages.

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Why Transcribe in Your Browser?

Most audio transcription services upload your audio to a remote server, process it there, and send back text. For a podcast interview or YouTube voiceover, that's fine. For a confidential client call, a deposition, a therapy session, a medical recording, or a private journal entry, it's a real privacy problem — you're handing sensitive audio to an unknown third party.

This tool is different. OpenAI released Whisper — the same speech recognition model that powers many premium transcription services — under the MIT license, with the model weights fully open source. Combined with Transformers.js (Hugging Face's library that runs ML models directly in browsers via WebAssembly and WebGPU), the entire pipeline can run on your device.

The first time you transcribe something, the model file downloads (40–250MB depending on which you pick) and caches in your browser. After that, you can disconnect from the internet entirely and the tool still works. Audio never touches a server — not ours, not OpenAI's, not anyone's.

Working from a video? Strip the audio track first with the Audio Extractor — Whisper handles the resulting MP3/WAV/AAC/OGG directly. And if your source video is too big to load comfortably, run it through the Video Compressor first to drop it to a manageable size before extraction. Once you have an SRT or VTT, the Subtitle Studio lets you fix any misheard words, retime drifting captions, and convert between subtitle formats before you publish. If you'd rather skip the manual chain and just get a captioned video back, the Video Auto-Subtitle tool combines this exact Whisper pipeline with FFmpeg.wasm subtitle burn-in.

Choosing the Right Model

Whisper comes in several sizes. Larger models are more accurate but take longer to download and run. Here's the trade-off:

Tiny (~40MB)
~90% accuracy
Fastest. Good for quick notes, voice memos, and casual content. Default choice for first-time users — fastest download.
Base (~75MB) ★
~94% accuracy
Recommended for most use cases — podcasts, meetings, interviews. Best balance of speed and accuracy.
Small (~250MB)
~96% accuracy
Highest accuracy that runs comfortably in-browser. Use for professional transcripts, legal recordings, or audio with accents or background noise.

.en suffix variants (whisper-tiny.en, whisper-base.en) are trained on English-only data and run slightly faster with marginally better English accuracy. Use the non-suffixed versions for any other language or mixed-language audio.

Common Use Cases

Podcast & Video Subtitles
Export SRT or VTT files ready to drop into YouTube, Premiere, Final Cut, or DaVinci Resolve. Word-level timestamps available for tight subtitle editing.
Meeting & Interview Notes
Drop a Zoom recording, get a searchable transcript. Useful for journalism, qualitative research, customer-discovery interviews, and 1:1 sync notes.
Voice Memos to Text
Record on your phone, drop the file here, get clean text. Faster than typing for long-form drafting, journaling, and capturing ideas while walking or driving.
Lecture & Class Notes
Students transcribe lectures, study sessions, or recorded discussions. Searchable text makes review and citation far easier than scrubbing audio.
Multilingual Content
99 languages supported. Useful for translating foreign-language audio, transcribing interviews in non-English languages, or generating subtitles for international content.
Private & Confidential Audio
Therapy notes, legal depositions, medical recordings, internal HR meetings — anything where uploading to a third-party transcription service is a privacy or compliance concern.

How We Compare

Honest read on free, paid, and self-hosted options for transcription:

UDT Audio Transcription (this tool): Free, browser-based, runs Whisper locally. No time limits, no upload, 99 languages. Limitation: large files (1+ hour) need patience on slower devices; max practical file size ~200MB.
Otter.ai: 300 free minutes/month, then $17/month for 1,200 minutes. Cloud-based — audio uploaded to Otter servers. Great for live meetings with speaker separation, but the privacy story is weaker.
Rev.com: $1.50/min for human transcription, $0.25/min for AI. Highest accuracy on the market for human, but at $90/hour vs free, only worth it for legal/medical use cases.
OpenAI Whisper API: $0.006/minute. Same model as this tool, but you upload audio to OpenAI's servers and pay per request. Faster than browser-based; not free; privacy depends on OpenAI's data policies.
Self-hosted Whisper: Free if you have a GPU. Faster than browser-based. Requires Python, CUDA, and command-line comfort. This tool gets you 80% of self-hosted's speed with zero setup.

Frequently Asked Questions

Is this tool really free?+
Yes — completely free with no time limits, no file size caps, no watermarks, and no signup. Most browser-based transcription services either cap free use at a few minutes per day or upload audio to their servers. This tool does neither. The site is supported by ads and affiliate links elsewhere; the tools themselves are unrestricted.
Is my audio uploaded to any server?+
No. The entire transcription runs in your browser using OpenAI's Whisper model (MIT-licensed, open source) loaded via Transformers.js. The model file downloads once and caches locally. After the first load, the tool works offline.
Why does it download a model the first time?+
Whisper is a neural network — the model file contains the trained "knowledge" needed to convert speech to text. It downloads once (40MB for tiny, up to 250MB for small) and caches in your browser. All subsequent transcriptions run from the cached copy without any network activity.
What languages are supported?+
99 languages with the multilingual models — including English, Spanish, French, German, Italian, Portuguese, Russian, Chinese, Japanese, Korean, Arabic, Hindi, and many more. For English-only audio, the English-tuned variant is faster and slightly more accurate.
How accurate is browser-based Whisper?+
The tiny model gets ~90% accuracy on clear English speech and is fast. The base model gets ~94% and is the recommended balance. The small model gets ~96% but is slower. Whisper handles accents, background noise, and technical vocabulary noticeably better than older speech-to-text systems.
Does it handle accents and background noise?+
Whisper was trained on 680,000 hours of diverse audio and handles accents, dialects, and moderate background noise well. The base or small models are recommended over tiny for non-native speakers, heavy accents, or noisy recordings.
What audio formats are supported?+
MP3, WAV, M4A, OGG, FLAC, WebM, and any format your browser's Web Audio API can decode. Video files like MP4 and MOV also work — the audio track is extracted automatically. Maximum recommended file size is around 200MB.
What's the maximum audio length?+
There's no hard limit. Transcription happens in 30-second chunks, so a 2-hour audio file processes the same way as a 2-minute one — just longer. Files over ~200MB may strain browser memory on older devices.
Can I get timestamps for subtitles?+
Yes. The tool produces segment-level timestamps and exports to SRT and VTT formats, ready for YouTube, Premiere, Final Cut, DaVinci Resolve, or any subtitle editor. Word-level timestamps are also available as an option.
Can it separate speakers (diarization)?+
Not yet — Whisper transcribes speech but doesn't label "Speaker 1" vs "Speaker 2." For meetings or interviews where speaker labels matter, consider Otter.ai or a Whisper + pyannote-audio pipeline (advanced, requires Python).
Can I edit the transcript?+
Yes — click any segment to edit the text inline. Edits persist in the export. For heavier editing, copy the plain text into your preferred editor.
How long does transcription take?+
On a modern laptop with the tiny model, transcription runs at roughly 5–10x real-time speed — a 10-minute recording takes about 1–2 minutes. The base and small models are slower but more accurate. On WebGPU-capable browsers (Chrome, Edge) the speed-up is significant.
Do I need a fast computer?+
Any device with 4GB+ RAM and a modern browser will work. WebGPU acceleration (Chrome, Edge) makes it significantly faster but is not required. The tool runs on phones and tablets, though desktops handle large files more comfortably.
Does it work on phones?+
Yes, on modern phones (2022+). Performance is roughly 2–3x slower than a laptop. Tiny model recommended on mobile. iOS Safari occasionally has memory issues with large audio files — Chrome on Android typically handles them better.
What's WebGPU and do I need it?+
WebGPU is a newer browser API that lets web apps use your GPU for ML workloads. When available (Chrome 113+, Edge 113+), transcription runs 3–10x faster. The tool falls back to WebAssembly automatically if WebGPU is unavailable, so it works everywhere — just slower without it.

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