{"id":105165,"date":"2022-09-25T21:36:38","date_gmt":"2022-09-25T19:36:39","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/otkryt-kod-sistemy-raspoznavaniya-i-perevoda-rechi-whisper"},"modified":"2022-09-25T21:36:38","modified_gmt":"2022-09-25T19:36:39","slug":"otkryt-kod-sistemy-raspoznavaniya-i-perevoda-rechi-whisper","status":"publish","type":"post","link":"https:\/\/prohoster.info\/hr\/blog\/news\/otkryt-kod-sistemy-raspoznavaniya-i-perevoda-rechi-whisper","title":{"rendered":"Otvoren je kod sustava prepoznavanja i prijevoda govora Whisper.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Projekt OpenAI, koji se bavi razvojem javnih projekata u podru\u010dju umjetne inteligencije, objavio je rezultate vezane uz sustav prepoznavanja govora Whisper. Tvrdnja je da sustav osigurava razine pouzdanosti i to\u010dnosti automatskog prepoznavanja govora na engleskom jeziku koje su bliske prepoznavanju od strane ljudi. Izvorni kod referentne implementacije temeljen na PyTorch okviru i skup ve\u0107 obu\u010denih modela koji su spremni za kori\u0161tenje su otvoreni. Kod je otvoren pod MIT licencom. <\/p>\n

Za obuku modela kori\u0161teno je 680 tisu\u0107a sati audio podataka prikupljenih iz nekoliko zbirki koje obuhva\u0107aju razli\u010dite jezike i tematska podru\u010dja. Oko 1\/3 kori\u0161tenih audio podataka tijekom obuke odnosi se na jezike razli\u010dite od engleskog. Predlo\u017eeni sustav ispravno obra\u0111uje situacije poput izgovora s naglaskom, prisutnosti pozadinske buke i kori\u0161tenja tehni\u010dkog \u017eargona. Osim transkripcije govora u tekst, sustav tako\u0111er mo\u017ee prevoditi govor s bilo kojeg jezika na engleski jezik i prepoznati pojavu govora u zvu\u010dnom toku. <\/p>\n

Modeli su formirani u dva prikazivanja: model za engleski jezik i vi\u0161ejezi\u010dni model koji podr\u017eava, izme\u0111u ostalog, ruski, ukrajinski i bijeloruski jezik. Svako prikazivanje je dodatno podijeljeno na 5 varijanti, koje se razlikuju prema veli\u010dini i broju parametara obuhva\u0107enih u modelu. \u0160to je ve\u0107a veli\u010dina, to je ve\u0107a to\u010dnost i kvaliteta prepoznavanja, ali i ve\u0107i zahtjevi za veli\u010dinom video memorije GPU-a te ni\u017ea performansa. Na primjer, minimalna varijanta uklju\u010duje 39 milijuna parametara i zahtijeva 1 GB video memorije, dok maksimalna uklju\u010duje 1550 milijuna parametara i zahtijeva 10 GB video memorije. Minimalna varijanta je 32 puta br\u017ea od maksimalne.

\"Otvoren<\/center> <\/p>\n

Sustav koristi arhitekturu neuronske mre\u017ee «Transformer», koja uklju\u010duje me\u0111usobno povezane kodere i dekodere. Zvuk se dijeli na 30-sekundne isje\u010dke, koji se pretvaraju u log-Mel spektrogram i \u0161alju koderu. Rezultat rada kodera se proslje\u0111uje dekoderu, koji predvi\u0111a tekstualnu reprezentaciju, pomije\u0161anu s posebnim tokenima, koji omogu\u0107uju rje\u0161avanje takvih zadataka u jedinstvenom modelu kao \u0161to su odre\u0111ivanje jezika, pra\u0107enje kronologije izgovora fraza, transkripcija govora na razli\u010ditim jezicima i prevo\u0111enje na engleski jezik.
\n
Izvor: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u041f\u0440\u043e\u0435\u043a\u0442 OpenAI, \u0437\u0430\u043d\u0438\u043c\u0430\u044e\u0449\u0438\u0439\u0441\u044f \u0440\u0430\u0437\u0432\u0438\u0442\u0438\u0435\u043c \u043e\u0431\u0449\u0435\u0434\u043e\u0441\u0442\u0443\u043f\u043d\u044b\u0445 \u043f\u0440\u043e\u0435\u043a\u0442\u043e\u0432 \u0432 \u043e\u0431\u043b\u0430\u0441\u0442\u0438 \u0438\u0441\u043a\u0443\u0441\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0433\u043e \u0438\u043d\u0442\u0435\u043b\u043b\u0435\u043a\u0442\u0430, \u043e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043b \u043d\u0430\u0440\u0430\u0431\u043e\u0442\u043a\u0438, \u0441\u0432\u044f\u0437\u0430\u043d\u043d\u044b\u0435 \u0441 \u0441\u0438\u0441\u0442\u0435\u043c\u043e\u0439 \u0440\u0430\u0441\u043f\u043e\u0437\u043d\u0430\u0432\u0430\u043d\u0438\u044f \u0440\u0435\u0447\u0438 Whisper. \u0423\u0442\u0432\u0435\u0440\u0436\u0434\u0430\u0435\u0442\u0441\u044f, \u0447\u0442\u043e \u0434\u043b\u044f \u0440\u0435\u0447\u0438 \u043d\u0430 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PyTorch \u0438 \u043d\u0430\u0431\u043e\u0440 \u0443\u0436\u0435 \u043e\u0431\u0443\u0447\u0435\u043d\u043d\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439, \u0433\u043e\u0442\u043e\u0432\u044b\u0445 \u0434\u043b\u044f \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f. \u041a\u043e\u0434 \u043e\u0442\u043a\u0440\u044b\u0442 […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":105166,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-105165","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47Otvoren kod sustava prepoznavanja i 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