Audio to Text

Transcribe audio to text, SRT, or VTT in your browser with Whisper. No upload, no signup, no watermark.

Drop an audio file here

or click to select a file

MP3, WAV, M4A, AAC, OGG, FLAC…

Runs 100% in your browser — the audio engine and the Whisper model download on first use and are cached afterwards. Your file never leaves your device.

What is Audio to Text?

Audio to Text is a free, browser-based transcription tool that turns spoken audio — podcasts, interviews, voice memos, meetings — into written text. It runs OpenAI's Whisper speech-recognition model entirely on your device, so nothing is uploaded, and exports the transcript as plain text, SRT, or VTT subtitles.

How to use

  1. Drop an audio file (MP3, WAV, M4A, AAC, OGG, FLAC…).
  2. Choose a language (or leave Auto-detect) and a model — Fast, Balanced, Accurate, or Max (best accuracy, WebGPU).
  3. Click Transcribe, then copy or download the text as TXT, SRT, or VTT.

Frequently asked questions

How do I convert audio to text for free?

Drop your MP3, WAV, or M4A file, pick a language and model, then click Transcribe. The tool runs OpenAI Whisper directly in your browser and gives you the transcript as plain text, SRT, or VTT. Nothing is uploaded and there is no signup.

Can I transcribe an MP3 or voice memo without uploading it?

Yes. Everything runs locally in your browser using a Whisper model compiled to run on your device. Your audio never leaves your computer, which makes it safe for interviews, voice memos, and other private recordings.

What audio formats are supported?

MP3, WAV, M4A, AAC, OGG, FLAC, and any other audio your browser can decode. The audio is resampled to 16 kHz mono before transcription, which is the format Whisper expects.

How accurate is the transcription?

Accuracy depends on the model you pick and the audio quality. The Max (large-v3-turbo) model is the most accurate — great for accents, proper nouns, and technical terms — and needs WebGPU; Accurate (small) is a good CPU-friendly middle ground, while Fast (tiny) trades accuracy for speed. Clear speech with little background noise gives the best results in any mode.

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