Free Kicheki Transcription
Transcribe Kicheki audio and video to text with AI. Fast, accurate, and free.
Jinsi Inavyofanya Kazi
- Nendeni kwenye mikutano Free.ai Transcriber
- Upload your Kicheki audio or video file
- Our AI automatically detects Kicheki and transcribes it
- Pakua nakala zako zikiwa maandishi au maandishi madogo - madogo ya SRT
Kicheki Transcription Features
- ✓Imepewa madaraka ya haraka zaidi (kibali cha MIT)
- ✓Automatic Kicheki language detection
- ✓Waunga mkono WaP3, WAV, MP4, M4A, FARAC, na wengine wengi
- ✓Nyakati ndogo - ndogo na maandishi ya siri yanayouzwa nje ya nchi (SRT)
- ✓Hakuna mipaka ya ukubwa wa faili juu ya mipango ya kulipwa
- ✓Mafaili ya kibinafsi na salama; mafaili hufutwa baada ya kutayarishwa
Maelezo ya Lugha
| Lugha | Kicheki |
| paper size | cs |
| Kioo cha AI | Mwizi wa haraka |
| Bei | Huru |
Lugha Zaidi
Ona Lugha ZoteFAQ
Whisper large-v3-turbo handles Kicheki solidly — 7-15% word error rate on benchmark audio. Expect occasional substitutions on named entities, numbers, and dense technical vocabulary; the bulk of the transcript will be correct. (Tier B, 7-15% word error rate on benchmark sets — we publish honest WER tiers rather than marketing claims.)
Yes — Kicheki transcription draws from your daily free token pool first. Audio costs about 50 tokens per minute, so the anonymous daily pool covers a few hours of audio per day. Signed-in accounts get a larger pool plus 10,000 signup tokens. Past that, $1 buys 750,000 tokens (~250 hours of audio).
Kicheki transcripts are returned in standard UTF-8 with the language's normal orthography.
MP3, WAV, M4A, FLAC, OGG, OPUS, and WEBM are accepted directly. For video (MP4, MOV, MKV) we extract the audio track server-side before sending it to Whisper — you do not need to convert anything yourself. Same pipeline regardless of source language, including Kicheki.
Anonymous uploads cap at roughly 500 MB per file. Signed-in accounts go up to 2 GB. Duration is not a hard limit — long files are chunked automatically (30-second windows with overlap) and stitched back into a single transcript with continuous timestamps. Multi-hour Kicheki recordings (podcasts, full lectures, meetings) work fine.
Yes — speaker diarization is on by default for every Kicheki transcript. The output is segmented as Speaker 1 / Speaker 2 / Speaker 3 with timestamps, so interviews, panel discussions, and multi-party meetings come back labeled. Diarization runs on a separate model and works the same across all languages we support.
Yes — paste the URL into /transcribe/youtube/ for YouTube or /transcribe/podcast/ for podcast feeds (Apple, Spotify, RSS). We download the audio, run it through Whisper with language=cs, and return the transcript with timestamps and speaker labels. Typical Kicheki content: lectures, interviews, voice notes, and YouTube content in Kicheki all work — paste a URL into /transcribe/youtube/ or upload the file directly.
Kwa kuwa gharama ni kama ishara 50 kwa dakika moja za kusikiliza, kwa hiyo kurekodi kwa saa moja ni ishara ya kila dakika. dola 1 inanunua kadi 750,000, ambazo hufanya kazi hadi muda wa saa 250 kwa dola. Watumiaji wengi hawatumii kamwe chochote kile chochote kile kilicho bure kila siku hufunika vidoka vifupi, sauti, na kipande kimoja cha sauti.
Yes — both segment-level (every ~10-30 seconds) and word-level timestamps are available. Word-level is the default for VTT/SRT subtitle export so the captions sync line-by-line. On the API set timestamps="word" in the request body. Kicheki transcripts are returned in standard UTF-8 with the language's normal orthography.
Yes. POST audio (multipart/form-data, field name "file") to /v1/transcribe/ with language=cs — or omit the language parameter to let Whisper auto-detect. Returns JSON with the transcript, segments, timestamps, and speaker labels. Full reference and SDK snippets at /api/.
Yes — once transcription finishes, click Translate or paste the text into /translate/. Kicheki pairs with every other language we support (200+). For meeting minutes pipe the transcript through /summarize/; for dubbing send it to /voice/tts/ to render audio in the target language.
Whisper is trained on hundreds of thousands of hours of real-world audio, so it tolerates background noise and phone-quality recordings on Kicheki. For best results, supply clean audio (headset mic, no music bed) — at this tier noise compounds the baseline error rate.Kama nakala itarudi nyuma bila kuweza, barua pepe wasiliana na@free.ai kwa faili tutarekebisha alama hizo na kuangalia kama injini tofauti inashika sauti yako vizuri zaidi.