I-isi-Nepali yokudlulisa
Bhala isi-Nepali umsindo nevidiyo ube ngumbhalo nge-AI. Ishesha, ilungile, futhi imahhala.
Indlela esebenza ngayo
- Iya ku- Umshicileli we-Free.ai
- Layisha phezulu ihele lakho le-isi-Nepali lomsindo noma levidiyo
- I-AI yethu ithola ngokuzenzakalela i-isi-Nepali futhi ibhalela
- Layisha ngezansi incwadi yakho njengesihloko noma isizinda se-SRT
isi-Nepali Izici zokudlulisa
- ✓Isebenza nge faster-whisper (ilayisense le-MIT)
- ✓Ukuthola ulwimi isi-Nepali ngokuzenzakalela
- ✓Isekela i-MP3, i-WAV, i-MP4, i-M4A, i-FLAC, nezinye
- ✓Ama-timestamps kanye ne-subtitle export (SRT)
- ✓Akukho kuphikiswa kwesayizi yefayela kuma-plans akhokhelwayo
- ✓Imfihlo nokuphepha -- amafayela asuswa ngemuva kokusebenza
Iminingwane yesilimi
| Ilimi | isi-Nepali |
| Ikhodi ISO | ne |
| Imodeli AI | faster-whisper |
| Intengo | Ikhululekile |
Izilimi Eziningi
Bona zonke izilimiImibuzo ebuzwa kaningi
isi-Nepali iyisilimi esincane-somthombo se-Whisper — i-large-v3-turbo ihlala ngaphezu kwe-25% yezinga lephutha legama, ngamanye amaxesha liphezulu kakhulu. I-transcript isebenza ukukhangela nokwenza i-gist kodwa akufanele ithathwe njengeshicilelwa-kulungile. Uma i-engine esezingeni eliphakeme itholakala ku-isi-Nepali siyibeka ngokuzenzakalela.(I-Tier D, over 25% word error rate kusethingi se-benchmark — sishicilela ama-tiers we-WER athembekile ngaphezu kokuphikisana nokumaketha.)
Yebo — isi-Nepali ukudluliswa kuqala kuvela ku-token pool yakho yansuku zonke. Umsindo ubiza ama-token angama-50 ngomzuzu, ngakho-ke i-token pool engaziwayo ihlanganisa amahora ambalwa we-audio ngosuku. Ama-akhawunti abhalisiwe athola u-token pool omkhulu wama-30,000 ngosuku. Ngaphakathi, ukudluliswa kwenziwa ngemali-njengoba-uhamba, nge-token top-ups kusuka ku-$1.
isi-Nepali izibhalo zibuyiselwa ngesikripthi seDevanagari (UTF-8).
MP3, WAV, M4A, FLAC, OGG, OPUS, ne WEBM zivunyelwe ngokuqondile. Ngevidiyo (MP4, MOV, MKV) sikhipha umsindo we-server-side ngaphambi kokuthunyelwa ku-Whisper — awudingi ukushintsha noma yini ngokwakho. Ipayipi elifanayo ngaphandle komthombo we-language, kufaka phakathi i-isi-Nepali.
Ukufaka okungenagama kufinyelela kuma-500 MB ngefayela ngalinye. Ama-akhawunti abhalisiwe afinyelela ku-2 GB. Ukuphela kwesikhathi akuyona umkhawulo onzima - amafayela ade ahlukaniswa ngokuzenzakalela (amafasitela emizuzu engu-30 ahlukaniswe) futhi aphinde ahlukaniswe ibe yi-transcript eyodwa nesikhathi esiqhubekayo. Ukurekhodwa kwehora eliningi isi-Nepali (amapodcasts, izifundo ezigcwele, izinhlanganiso) kusebenza kahle.
Yebo — ukudweba umsindo komsindo kusetshenzisiwe ngokuzenzakalela kuwo wonke ama-isi-Nepali transcript. I-output ihlukaniswe njenge-Speaker 1 / Speaker 2 / Speaker 3 nge-timestamps, ngakho-ke izingqungquthela, izingqungquthela zepaneli, nezingqungquthela zeqembu eliningi zibuyela emuva zinikezwe i-label. Ukudweba umsindo kusebenza ngemodeli ehlukile futhi kusebenza ngokufanayo kuwo wonke ama-languages esiwaxhasayo.
Yebo — chofoza i-URL ku /transcribe/youtube/ ye-YouTube noma /transcribe/podcast/ ye-podcast feeds (Apple, Spotify, RSS). Silanda umsindo, siwuqhube nge-Whisper nge-language=ne, futhi sibuyisele i-transcript nge-timestamps ne-speaker labels. I-isi-Nepali ejwayelekile: izifundo, izingqungquthela, izimemo zomsindo, kanye ne-YouTube isi-Nepali zonke zisebenza — chofoza i-URL /transcribe/youtube/ noma ulayishe ifayela ngqo.
Whisper ibiza ama-token angama-50 ngomzuzu wokudlalwa kwesandi, ngakho-ke ukurekhoda kwehora elilodwa kubiza ama-token angama-~3,000. Abaningi abasebenzisayo abasebenzisi lutho — i-pool yamahhala yansuku zonke yama-token angama-30,000 ifaka ama-clip ancane, ama-notes omsindo, nama-podcasts afanayo. Ngaphesheya kwayo, ukudluliswa kwenziwa ngemali-njengoba-uhamba, nge-token top-ups kusuka ku-$1.
Yebo — zombili isigaba-sezinga (noma yikuphi ~10-30 imizuzwana) kanye negama-level timestamps zikhona. Igama-level yiphutha le-VTT/SRT subtitle export ngakho ama-captions asynchronize line-by-line. Kwi-API hlela timestamps="word" kwi-body yesicelo. isi-Nepali izibhalo zibuyiselwa ngesikripthi seDevanagari (UTF-8).
Yebo. POST umsindo (ingxenye/ifomu-data, igama lendawo "ihele") ku /v1/transcribe/ nge lingu=ne — noma ushiye i parameter yesilimi ukuze i Whisper ikwazi ukukhomba ngokuzenzakalela. Ibuyisela i JSON nge lingu, amasegmenti, ama-timestamps, nama-speaker labels. Umbiko ophelele kanye ne-SDK snippets ku /api/.
Yebo — uma ukuguqulelwa kuqediwe, chofoza guqula noma chofoza umbhalo ku /guqula/. isi-Nepali ixhumana nanoma iyiphi enye ulwimi esixhasayo (200+). Usuku lwengxoxo lidlulisa ukuguqulelwa /summarize/; ukuguqulelwa lithunyelwe ku /voice/tts/ ukuze kunikezwe umsindo kulimi oluzosetshenziswa.
Whisper's noise training helps less at this tier — the bottleneck is the amount of isi-Nepali audio Whisper saw during training, not noise. Clean studio audio still beats noise audio, but neither will reach the accuracy you would get on a high-source language.Uma i-transcript ibuyela ingasebenzi, thumela i-imeyili ku contact@free.ai ngefayela — sizobuyisela imali ye-token futhi sibheke ukuthi ngabe i-engine eyahlukileyo iphatha umsindo wakho kahle.