Speech to Text, Done Right
Convert recorded speech — interviews, meetings, lectures, voice notes — into structured text with automatic speech recognition (ASR). ScribeToAny runs Whisper-class models on dedicated GPUs across ~98 languages, adds punctuation, and can label speakers; clear audio gives the best results.
- AI transcription
- 98 Languages
- Encrypted; we never train AI on your files
Start with your recording
Drop an audio or video file here, or click to choose.
What you get: a real transcript
Unedited output from a 64-second interview with two speakers (synthetic voices), transcribed with speaker detection on. Only the first lines are shown.
SPEAKER_00 (0:00) Welcome back to Small Shop Stories. SPEAKER_00 (0:02) Today I'm talking to Maya, who runs a tiny bakery on the SPEAKER_00 (0:05) corner of Mill Street. SPEAKER_01 (0:07) Thanks for having me. SPEAKER_01 (0:08) It's really small, just two ovens and a counter. SPEAKER_00 (0:12) So how does a normal day start for you?
1 00:00:00,000 --> 00:00:01,680 [SPEAKER_00] Welcome back to Small Shop Stories. 2 00:00:02,160 --> 00:00:05,320 [SPEAKER_00] Today I'm talking to Maya, who runs a tiny bakery on the 3 00:00:05,320 --> 00:00:06,320 [SPEAKER_00] corner of Mill Street.
Checked against the script, 4 of 189 words differed — a 2.1% word error rate, counting "80" written for "eighty" as an error — and all 14 speaker turns were labelled correctly. This was clean speech; noisy recordings and people talking over each other score lower. See the full transcript and how it was scored
How it works
- 1
Upload
Drop in an audio or video file, or paste a link. All common formats are accepted.
- 2
Transcribe
AI transcribes with timestamps and optional speaker labels, usually in minutes.
- 3
Export
Edit segments online, then export TXT, SRT, VTT, TSV, CSV, JSON, PDF or DOCX.
Why ScribeToAny
- Automatic speech recognition (ASR) with Whisper-class models across ~98 languages, strongest on clear, well-recorded speech.
- Automated speaker diarization labels distinct voices (Speaker 1, Speaker 2) across meetings, panels, and one-on-one interviews.
- Punctuation, capitalisation and sentence breaks are added automatically, so spoken thoughts read as paragraphs.
Frequently asked questions
How does AI speech recognition differ from simple audio file conversion?
File conversion simply re-encodes sound bytes between formats (like WAV to MP3). Speech recognition (ASR) uses deep neural networks to decode human acoustics into written vocabulary, distinguish phonetic boundaries, automatically insert punctuation, and separate speakers into readable dialogue.
Is this live dictation or file transcription?
File transcription. You upload or record audio and receive a complete, timestamped transcript. Because the model sees the whole recording, it can use the surrounding context — usually more accurate than tools that must guess word by word as you speak — and you get speaker labels, segment editing and 8 export formats on top.
Is my audio private?
Yes. Files upload over HTTPS directly to encrypted cloud storage and are visible only to your account. We never train AI on your files. Transcripts stay private unless you explicitly create a read-only share link, which you can revoke at any time. You can also permanently delete any file or transcript from the workspace whenever you choose.
Are filler words like "um" and "uh" kept?
Usually not. Whisper-class models tend to write clean verbatim: most fillers, false starts and repeated words are left out, which makes the text easier to read. If you need strict verbatim — for research coding, for example — add them back in the editor while replaying the audio.
Can I speak into my microphone instead of uploading a file?
Yes — use Record audio in your workspace. It records in the browser, then transcribes the recording with the same options as an upload. It isn't live captioning: the text appears after you stop recording, which is also why it can use the whole recording for context.