Fitar da saƙonka na murya azaman MP3 ko WAV daga app ɗin saƙon murya na mai ɗaukar waya, akwatin saƙon VoIP, ko tsarin PBX. Ka sauke fayil ɗin kuma ka sami rubutu mai lokaci cikin daƙiƙa.
MP3 · WAV · M4A · MP4 · MOV · MKV · OGG · OPUS · FLAC · WEBM — up to 100 MB anonymously
YouTube · TikTok · Vimeo · Twitter · SoundCloud · Spotify · 50+ more
↓ Watch what happens
Drop a file, paste a URL, or record live — text appears back with speaker labels and timestamps. Same pipeline whether the source is a file, a URL, or your microphone.
Thanks for making the time. I want to start with framing — what was the original hypothesis behind the project?
Honestly, maybe forty percent. The shape held — the mechanics underneath had to be rebuilt almost entirely.
What flipped it for you? Was there one customer call, one piece of data
↓ This is the dashboard
Same layout as the real dashboard — Summary, full Transcript, Speakers tab, Exports. Key points and action items extracted automatically. Auto-tags on every job.
Sample preview from a founder interview about post-call workflow. Real transcripts look exactly like this — same tabs, same summary block, same key-points / action-items split, same auto-tag chips.
Three real options · honest comparison
Three legitimate ways to get text from spoken audio in 2026. Each is best for different work. Honest numbers below — no claim that AI matches a professional human transcriber on hard audio.
Live, free, on-device. Handy for short bursts while you talk.
~30× faster than realtime. 100+ languages. Speaker labels. The sweet spot for most work.
Gold-standard accuracy when the audio is hard or the stakes are legal.
Built-in dictation figures from public iOS / Android speech API benchmarks. Human transcriber rates from US/UK industry surveys 2024–2025.
Accuracy · real-world numbers
Modern transcription reaches 95%+ word accuracy on clear English at 128 kbps and above, comparable to a human transcriber on the same recording. The audio coming in sets the ceiling — cleaner source, cleaner transcript. The breakdown below covers the recordings we actually see in production.
USB or studio microphone in a treated room. Single speaker at conversational distance. The headline number.
Podcast masters, interview recordings, well-mic'd meetings. The sweet spot for most professional work.
Field-recorded interviews, podcast episodes at 64–128 kbps, multi-speaker recordings. Usable for editorial without a review pass.
Ceiling mic, omnidirectional capture, mild reverb, multiple speakers at distance. Plan a rename pass on the speaker chips.
Common questions
Mintuna 30 kyauta a wata, babu katin. Sauke saƙon murya ɗaya, sauke MP3 ko WAV — rubutu cikin kimanin daƙiƙa 10.
Fara rubutu kyauta