Free Tool

Audio to Text: Transcribe Audio and Voice Recordings

Upload an audio or video file and get a text transcript with speaker labels and timestamps, ready to copy or download as TXT, Word, SRT or VTT. The first file is free up to 30 minutes with no account. MeetWave runs the same speech-to-text engine it uses for meeting recordings, and deletes your audio as soon as the transcript is ready.

First file free up to 30 min · then 1 credit per 30 min (from $0.06) · New accounts get 3 credits

What you get

A transcript split into short lines, each with the time it was spoken and the speaker who said it. The speaker labels come from a diarization model that runs after the speech-to-text engine: it groups the voices it hears and names them Speaker 1, Speaker 2 and so on. Click a label to replace it with a real name, and every export uses the new name.

Above the transcript you can search for a word, show only one speaker, or jump to a timestamp. The Copy button puts the whole text on your clipboard with speaker names. Download gives you the same text as plain text, text with timestamps, SRT or VTT subtitles you can load into a video player, a Word document, Markdown for Notion or Obsidian, or a PDF.

Which formats work

Most recordings can be uploaded exactly as they come off the device — there is no need to convert them to MP3 first. The engine decodes the file on the server, video included, and only the sound is transcribed.

Where the recording comes fromUsual file type
iPhone Voice Memos.m4a
WhatsApp voice message.opus
Telegram voice message.ogg
Zoom local recording.m4a (audio only) or .mp4 (with video)
Dictaphone or field recorder.wav or .mp3
Screen recording or phone video.mp4 or .mov

The upload limit is 350 MB. Speech-only audio is usually well within it; video is not — a few minutes of high-resolution phone video can already be too large. For a long video, open it in MeetWave instead: the app pulls the audio out of the video in your browser before uploading.

What happens to your file

You do not need an account, so we keep as little as possible and for as short a time as possible. The transcript is not used to train any model, and nothing about its content goes into our logs or analytics.

WhatWhere it is keptHow long
Your audio or video fileEncrypted storage used only for this jobUntil the transcript is ready, then deleted — every stored version of it
The working copy on the transcription serverThe server that runs the speech-to-text engineDeleted together with the file
The transcriptEncrypted storage, under a random job id24 hours, or until you click "Delete now"; a storage rule removes anything left within 48 hours
The file nameOnly in your browser, so a reload can show itNever sent to us

Getting a clean transcript

Most of the accuracy is decided when the audio is recorded, not when it is transcribed. Three things matter most. The distance to the speaker: a phone or microphone within arm's length gives clear words, one across the room gives gaps. Background noise: music, traffic and a humming air conditioner compete with speech. Crosstalk: when two people talk at once, both lines suffer and the speaker labels can merge.

If you record the file yourself, a few seconds of test recording played back before the real thing catches most problems. For a fuller walkthrough — from recording to editing the text — read the step-by-step guide to transcribing audio, and if you need to choose a paid service for regular work, compare transcription software before you buy.

Transcript vs meeting summary

A transcript is every word in order: right for quotes, interviews, subtitles and records. A summary is what the conversation decided — the points, decisions and action items — and for a one-hour meeting it is the difference between reading ten pages and reading one. This page gives you the transcript of a file you already have: the first 30 minutes free, then one credit per started 30 minutes. MeetWave meeting summaries start earlier: the app records your Zoom, Google Meet or Teams call without a bot joining it, and turns it into a summary with action items when the call ends.

How to convert audio to text

Step 1

Choose your file

Drag an audio or video file onto the page or pick it from your device: MP3, WAV, M4A, OGG, OPUS, FLAC, AAC, WMA, WEBM, MP4, MOV, MKV or AVI, up to 350 MB. The page reads its length before anything is uploaded.

Step 2

Start the transcription

Click Transcribe. The file goes straight to encrypted storage, and the speech-to-text engine starts. A timer shows how long you have been waiting; you can reload the page and the result will still arrive.

Step 3

Read, search and rename

The transcript appears line by line with timestamps and speaker labels. Search it, show one speaker at a time, and click a label such as "Speaker 1" to give it a real name.

Step 4

Copy or download — then delete

Copy the text or download TXT, SRT, VTT, Word, Markdown or PDF. The audio is already gone; the transcript is kept for 24 hours so a reload does not lose it, or delete it now with one click.

Frequently Asked Questions

Yes, the first file is free with no account: up to 30 minutes of it are transcribed, and a longer file gets its first 30 minutes with a note saying so. After that, signing up gives you 3 free credits, and a file costs one credit per started 30 minutes — a 45-minute recording is 2 credits. There is also a daily limit on free transcriptions for everyone together; when it is reached, the page offers the sign-up credits instead.

It is uploaded to encrypted storage used only for this job, transcribed, and deleted as soon as the transcript is ready — including the working copy on the transcription server. The transcript is kept for 24 hours so a page reload does not lose it; "Delete now" removes it immediately, and a storage rule deletes anything left within 48 hours. The file name stays in your browser, and neither the audio nor the text is used to train models.

The engine detects the spoken language by itself — there is nothing to choose. It is built on OpenAI Whisper large-v3-turbo, whose model card lists 99 languages (checked on 23 September 2026). Quality is best in widely spoken languages and on clear recordings; the transcript comes out in the language that was spoken, not translated.

Yes. After transcription a separate diarization model (pyannote speaker-diarization 3.1) works out who spoke when, and each line gets a label: Speaker 1, Speaker 2 and so on. Click a label to rename it — the new name is used in every download. Two people talking over each other, or very similar voices, can end up under one label.

It depends on the length of the file and on whether the transcription engine has to start up first — the first run after a quiet spell takes longer. While you wait, the page shows the elapsed time and an estimate based on the length of your file. You can reload the page or come back to it later the same day — the result will be there.

This tool gives you the transcript of one file you already have. MeetWave records your Zoom, Google Meet and Teams calls without a bot joining, then turns them into a summary with decisions and action items. You can open the same file in MeetWave to get that summary — the free plan includes 600 minutes of recordings a month.

Engine: Whisper large-v3-turbo model card (Hugging Face) · WhisperX (GitHub) · pyannote speaker-diarization-3.1 model card