Audio to Text
Transcribe MP3, WAV, M4A, voice memos, Zoom recordings, and podcasts in your browser. Speaker labels included. Export TXT, SRT, VTT. Free, no upload, no signup.
Your audio stays inside this browser tab, never reaches a server, and nothing is saved to your computer. The first visit downloads the AI models into your browser cache, about 210 MB once (300 MB in compatibility mode). After that they load from the cache.
Pick an audio or video file to transcribe.
Record from your mic, capture another browser tab, or upload an audio or video file. Click any "Speaker 1" label to rename it, and click any line's text to fix the wording before exporting. Clearing a line deletes it.
What is the Audio to Text?
Audio transcription converts spoken audio into a written text document. This tool runs OpenAI's Whisper-base.en model and a speaker-diarization pipeline directly in your browser via WebGPU or WebAssembly, so the audio file or microphone stream is never sent to a server. Each speaker is labeled (Speaker 1, Speaker 2, and so on) and the output can be exported as plain text, SRT subtitles, or WebVTT captions.
How to use the Audio to Text
- 1
Pick an input mode
Choose Microphone to record from your device, Browser tab to transcribe audio playing in a Chrome or Edge tab, or Upload file to pick an MP3, WAV, M4A, OGG, or WebM file.
- 2
Wait for the model to load
On first use, Whisper-base.en and the speaker-segmentation model download from Hugging Face, about 210 MB in total (300 MB on browsers without WebGPU). That takes a minute or two depending on your connection. Later visits load them from the browser cache.
- 3
Start and stop recording
Click Start recording. For microphone and browser tab, speak or play the audio, then click Stop. For file uploads, processing begins as soon as the models are ready. A progress bar shows how far it has got, and Cancel stops it at any point.
- 4
Review and rename speakers
The transcript appears with Speaker 1, Speaker 2 labels. Click any label to rename it (for example, to the person's actual name) before exporting.
- 5
Export the transcript
Download as TXT for plain text, SRT for video subtitle tracks, or VTT for web captions. SRT and VTT carry timestamps and are cut into short subtitle lines. TXT is plain paragraphs.
Works with
Meeting & call recordings
- •Zoom (cloud and local recordings)
- •Google Meet recordings
- •Microsoft Teams meeting recordings
- •Webex recordings
- •Discord call recordings
- •Slack huddle recordings
- •GoToMeeting and BlueJeans archives
Video platforms (via Browser tab mode)
- •YouTube videos
- •Vimeo videos
- •Loom screen recordings
- •Twitch stream replays
- •TikTok and Instagram Reels (when played in browser)
- •Any video playing in a Chrome or Edge tab
Audio file formats
- •MP3
- •WAV
- •M4A
- •OGG
- •WebM
- •FLAC
- •AAC
- •Opus
Mobile recordings
- •iPhone Voice Memos (.m4a)
- •Android voice recorder files
- •WhatsApp voice notes
- •Telegram voice messages
- •Field recordings from journalism apps
Content types
- •Podcasts and podcast interviews
- •University lectures and webinars
- •Journalist interviews and source recordings
- •Conference talks and panel discussions
- •Sermons and religious talks
- •Court depositions and legal recordings
- •Oral history and ethnographic research
- •Customer support call recordings
- •Sales call recordings for note-taking
Frequently Asked Questions
Is my audio uploaded to a server?
No. The Whisper model runs inside your browser using WebGPU (or WebAssembly as a fallback). Your microphone stream, tab audio, and uploaded files are processed locally and never sent anywhere. You can verify this by opening DevTools and checking the Network tab during transcription.
What audio file formats are supported?
MP3, WAV, M4A, OGG, and WebM, plus the audio track of MP4 and MOV videos. There is no server cap, but browsers refuse to decode more than about 90 minutes in one go, so split longer recordings into parts. Long files also use a lot of memory. A one hour file peaked at about 11 GB on our 32 GB test PC, so on a laptop with little RAM the tab may close.
What languages does it support?
English only for now. The model is Whisper-base.en, and speech in other languages comes out as garbled English with no warning. A multilingual Whisper model may be added in a future update.
Why is the first transcription slow?
The first run downloads Whisper-base.en and pyannote-segmentation-3.0 from the Hugging Face CDN, about 210 MB combined (300 MB on browsers without WebGPU). After that, both models stay in the browser cache and load in a few seconds on return visits.
How accurate is speaker diarization?
Speaker detection works best when speakers take distinct turns and there is minimal crosstalk. The model tells at most three voices apart, so anyone beyond that gets folded into one of the three labels, and heavy background noise or overlapping speech lowers accuracy. In a 30 minute test with two voices, about 94% of the speaking time went to the right person, but very short replies were right only about half the time. Treat the labels as a starting point and rename them before publishing.
Can I get a transcription with speaker labels for free?
Yes. Speaker labels are part of the standard output here, not a paid add-on. A recording with more than one voice comes back with Speaker 1, Speaker 2, and so on already assigned, and you can rename the labels before exporting to TXT, SRT, or VTT.
Can I transcribe a Zoom, Google Meet, or Microsoft Teams recording?
Yes, in two ways. If you already downloaded the recording (typical Zoom .m4a or .mp4 file), pick it in Upload file mode. If the meeting is currently playing back in a browser tab, switch to Browser tab mode (Chrome or Edge), share that tab, and tick "Share tab audio." Speaker labels make it easy to attribute who said what afterward.
Can I transcribe a voice memo from my iPhone or Android?
Yes. iPhone Voice Memos export as .m4a, Android phones typically save .m4a or .amr. AirDrop or share the file to a desktop browser, then pick it in Upload file mode. A 30 minute recording took about 4.5 minutes on a desktop PC with a dedicated graphics card and about 16.5 minutes in a browser without WebGPU, so a short memo is quick and a slower machine takes longer.
Can I transcribe a YouTube video?
Yes, using Browser tab mode in Chrome or Edge. Open the YouTube video in another tab, click Start recording, then pick that tab in the share dialog. The tool captures the tab's audio output directly. No browser extension required.
Is this a free alternative to Otter.ai, Rev, or Descript?
Yes. Otter, Rev, and Descript all send audio to their servers, require an account, and charge after a free quota. This tool runs everything locally in your browser, is free with no usage caps, and requires no signup. Speaker labels and SRT/VTT export are included.
How does the transcription quality compare to Otter.ai or Rev?
Whisper-base.en is a smaller model than what Otter and Rev use on their cloud, so on accented or noisy audio the word error rate is slightly higher. On clean studio-quality audio (podcasts, recorded meetings), accuracy is comparable. The trade-off you make is privacy and zero cost in exchange for a few percentage points of accuracy on hard audio.
Do I need real-time captions instead of a finished transcript?
Use the Live Transcription tool instead. It shows captions as you speak with around 500ms latency. Note that Live Transcription does not include speaker labels.