{"id":884,"date":"2026-08-11T11:20:29","date_gmt":"2026-08-11T11:20:29","guid":{"rendered":"https:\/\/sonix.ai\/ai\/?p=884"},"modified":"2026-08-11T20:00:49","modified_gmt":"2026-08-11T20:00:49","slug":"gpt5-vs-llama2","status":"publish","type":"post","link":"https:\/\/sonix.ai\/ai\/tr\/gpt-5-ve-llama-2-karsilastirmasi\/","title":{"rendered":"GPT-5 ve Llama 2: Hangi B\u00fcy\u00fck Dil Modeli (LLM) Transkripsiyonlu Metni En \u0130yi \u0130\u015fliyor?"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Sesli i\u00e7eriklerinizden i\u00e7g\u00f6r\u00fcler elde etmek i\u00e7in g\u00fc\u00e7l\u00fc bir b\u00fcy\u00fck dil modeline yat\u0131r\u0131m yapt\u0131n\u0131z, ancak \u00e7o\u011fu ki\u015finin g\u00f6zden ka\u00e7\u0131rd\u0131\u011f\u0131 bir nokta var: B\u00fcy\u00fck dil modelinizin zekas\u0131, transkriptinizin do\u011frulu\u011fu kadar. Herhangi bir geli\u015fmi\u015f dil modeli, toplant\u0131lar\u0131n\u0131z\u0131 \u00f6zetleyebilmek, r\u00f6portajlar\u0131 analiz edebilmek veya kay\u0131tlardan ana temalar\u0131 \u00e7\u0131karabilmek i\u00e7in \u00f6ncelikle \u00fczerinde \u00e7al\u0131\u015fabilece\u011fi temiz ve do\u011fru bir metne ihtiya\u00e7 duyar. Ara\u015ft\u0131rmalar, transkripsiyon hatalar\u0131n\u0131n sonraki a\u015famalardaki yapay zeka performans\u0131n\u0131 do\u011frudan etkiledi\u011fini do\u011frulamaktad\u0131r; bu da se\u00e7iminizi <\/span><a href=\"https:\/\/sonix.ai\/features\/automated-transcription\"><span style=\"font-weight: 400;\">otomati\u0307k transkri\u0307psi\u0307yon<\/span><\/a><span style=\"font-weight: 400;\"> LLM se\u00e7iminiz kadar \u00f6nemlidir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Peki, hangi model metin transkripsiyonunu daha iyi i\u015fliyor? Cevap, sizin \u00f6zel i\u015f ak\u0131\u015f\u0131n\u0131za, teknik gereksinimlerinize ve do\u011fruluk ihtiya\u00e7lar\u0131n\u0131za ba\u011fl\u0131d\u0131r. GPT-5, 400.000 tokenlik bir ba\u011flam penceresine ve metin ile g\u00f6r\u00fcnt\u00fc girdilerine sahip, piyasaya s\u00fcr\u00fclm\u00fc\u015f bir OpenAI modelidir; Llama 2 ise modelleri kendi altyap\u0131lar\u0131nda \u00e7al\u0131\u015ft\u0131rmak isteyen ekipler i\u00e7in indirilebilir a\u011f\u0131rl\u0131klar ve 4.096 tokenlik bir ba\u011flam penceresi sunar. Bu kar\u015f\u0131la\u015ft\u0131rma, her iki modeli de ayr\u0131nt\u0131l\u0131 olarak ele al\u0131yor ve transkripsiyon kalitesinin her iki modelde de ba\u015far\u0131y\u0131 neden belirledi\u011fini g\u00f6steriyor.<\/span><\/p>\n<h2><b>\u00d6nemli \u00c7\u0131kar\u0131mlar<\/b><\/h2>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">GPT-5, 400.000 tokenlik bir ba\u011flam penceresi desteklerken, orijinal Llama 2 modelleri 4.096 tokenlik bir ba\u011flam penceresi kullan\u0131r; bu da GPT-5\u2019i, par\u00e7alara ay\u0131rma yapmadan uzun transkriptleri analiz etmek i\u00e7in son derece uygun hale getirir<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Transkripsiyon hatalar\u0131, b\u00fcy\u00fck dil modelleri (LLM) analizinde yay\u0131lmaktad\u0131r: Ara\u015ft\u0131rmalar, konu\u015fma-metin d\u00f6n\u00fc\u015ft\u00fcrmede meydana gelen k\u00fc\u00e7\u00fck hatalar\u0131n bile sonraki a\u015famalardaki g\u00f6rev performans\u0131n\u0131 d\u00fc\u015f\u00fcrd\u00fc\u011f\u00fcn\u00fc g\u00f6stermektedir<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Geli\u015fmi\u015f dil modelleri, y\u00fcksek kaliteli girdilerde en iyi performans\u0131 g\u00f6sterir; ayr\u0131ca, hukuk, t\u0131p ve mevzuata uygunluk alanlar\u0131ndaki kullan\u0131m senaryolar\u0131nda transkripsiyon a\u015famas\u0131ndaki do\u011fruluk en \u00f6nemli fakt\u00f6rd\u00fcr<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Llama 2, kendi sunucusunda bar\u0131nd\u0131r\u0131ld\u0131\u011f\u0131nda \u00f6zelle\u015ftirme se\u00e7enekleri sunarak, \u00f6zel kelime da\u011farc\u0131\u011f\u0131 ve domain\u2019ye \u00f6zg\u00fc ihtiya\u00e7lara y\u00f6nelik ince ayarlamalara olanak tan\u0131r<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Sonix, \u015funlar\u0131 sunar:<\/span> <a href=\"https:\/\/sonix.ai\/features\/automated-transcription\"><span style=\"font-weight: 400;\">99%'ye kadar do\u011fruluk<\/span><\/a><span style=\"font-weight: 400;\"> net ses kalitesi sayesinde her iki modele de ihtiya\u00e7 duyduklar\u0131 temiz veriyi sa\u011fl\u0131yor; \u00e7\u00fcnk\u00fc hangi LLM\u2019yi se\u00e7erseniz se\u00e7in, \u201cgiri\u015f ne olursa \u00e7\u0131k\u0131\u015f da o olur\u201d<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Ba\u011flam penceresinin boyutu \u00f6nemlidir; zira daha uzun bir ba\u011flam, konu\u015fma tutarl\u0131l\u0131\u011f\u0131n\u0131 kaybetmeden transkriptlerin tamam\u0131n\u0131n analiz edilmesini sa\u011flar<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Sonix, a\u015fa\u011f\u0131dakilerde transkripsiyon deste\u011fi sunar: <\/span><a href=\"https:\/\/sonix.ai\/languages\"><span style=\"font-weight: 400;\">54'ten fazla dil<\/span><\/a><span style=\"font-weight: 400;\">, k\u00fcresel ekipler i\u00e7in \u00e7ok dilli transkripsiyon i\u015f ak\u0131\u015flar\u0131n\u0131 m\u00fcmk\u00fcn k\u0131lar<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Sonix art\u0131k salt okunur bir MCP sunucusu arac\u0131l\u0131\u011f\u0131yla yapay zeka asistanlar\u0131na, Sonix CLI arac\u0131l\u0131\u011f\u0131yla ise terminal ve CI i\u015f ak\u0131\u015flar\u0131na ba\u011flan\u0131yor<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Bulut tabanl\u0131 ve kendi sunucusunda bar\u0131nd\u0131r\u0131lan yakla\u015f\u0131mlar aras\u0131nda gizlilik ve da\u011f\u0131t\u0131m se\u00e7enekleri a\u00e7\u0131s\u0131ndan \u00f6nemli farkl\u0131l\u0131klar bulunmaktad\u0131r<\/span><\/li>\n<\/ul>\n<h2><b>B\u00fcy\u00fck Dil Modellerini Anlamak: GPT-5 ve Llama 2 A\u00e7\u0131klamas\u0131<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">B\u00fcy\u00fck dil modelleri, insan benzeri metinleri anlamak ve \u00fcretmek i\u00e7in devasa metin veri k\u00fcmeleri \u00fczerinde e\u011fitilmi\u015f sinir a\u011flar\u0131n\u0131 kullan\u0131r. Bu modeller, \u00f6zetleme, varl\u0131k \u00e7\u0131karma, duygu analizi ve soru yan\u0131tlama gibi g\u00f6revlerde \u00fcst\u00fcn performans g\u00f6sterir; bunlar da, transkripsiyonu yap\u0131lm\u0131\u015f ses ve video i\u00e7erikleriyle \u00e7al\u0131\u015f\u0131rken tam da ihtiyac\u0131n\u0131z olan \u00f6zelliklerdir.<\/span><\/p>\n<h3><b>B\u00fcy\u00fck Dil Modelleri Nedir?<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">LLM\u2019ler, metinleri transformer mimarisi arac\u0131l\u0131\u011f\u0131yla i\u015fleyerek ba\u011flam\u0131 anlamalar\u0131na, kal\u0131plar\u0131 tespit etmelerine ve tutarl\u0131 yan\u0131tlar \u00fcretmelerine olanak tan\u0131r. Bir toplant\u0131 tutana\u011f\u0131n\u0131 bir LLM\u2019ye girdi\u011finizde, bu sistem eylem maddelerini belirleyebilir, tart\u0131\u015fmalar\u0131 \u00f6zetleyebilir, ana temalar\u0131 ortaya \u00e7\u0131karabilir ve i\u00e7erikle ilgili sorular\u0131 yan\u0131tlayabilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Transkripsiyonlu i\u00e7eri\u011fin pratik uygulama alanlar\u0131 son derece geni\u015ftir:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Toplant\u0131 \u00f6zetleri<\/b><span style=\"font-weight: 400;\"> kararlar\u0131 ve sonraki ad\u0131mlar\u0131 belirleyen<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Ara\u015ft\u0131rma analizi<\/b><span style=\"font-weight: 400;\"> birden fazla g\u00f6r\u00fc\u015fme boyunca ortaya \u00e7\u0131kan kal\u0131plar\u0131 belirleyen<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>\u0130\u00e7eri\u011fin yeniden kullan\u0131m\u0131<\/b><span style=\"font-weight: 400;\"> uzun kay\u0131tlar\u0131 blog yaz\u0131lar\u0131 ve sosyal medya payla\u015f\u0131mlar\u0131na d\u00f6n\u00fc\u015ft\u00fcren<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Uyum denetimi<\/b><span style=\"font-weight: 400;\"> belirli konular\u0131 veya endi\u015feleri i\u015faretleyen<\/span><\/li>\n<\/ul>\n<h3><b>Temel Farkl\u0131l\u0131klar: Tescilli Yaz\u0131l\u0131m ve A\u00e7\u0131k Kaynak<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">GPT-5 ve Llama 2, b\u00fcy\u00fck dil modellerinin (LLM) devreye al\u0131nmas\u0131na y\u00f6nelik temelde farkl\u0131 yakla\u015f\u0131mlar\u0131 temsil etmektedir.<\/span><\/p>\n<p><b>GPT-5<\/b><span style=\"font-weight: 400;\"> OpenAI\u2019nin 7 A\u011fustos 2025 tarihinde piyasaya s\u00fcr\u00fclen ve OpenAI API arac\u0131l\u0131\u011f\u0131yla eri\u015filebilen tescilli modelidir. G\u00fc\u00e7l\u00fc bir ak\u0131l y\u00fcr\u00fctme performans\u0131 sunar ve hem metin hem de g\u00f6r\u00fcnt\u00fc girdilerini kabul eder; bu modeli kullanmak, verilerinizi OpenAI\u2019nin sunucular\u0131na g\u00f6ndermek anlam\u0131na gelir. OpenAI art\u0131k GPT-5\u2019i \u00f6nceki nesil bir model olarak tan\u0131mlamakta ve mevcut projeleri daha yeni GPT-5.x s\u00fcr\u00fcmlerine y\u00f6nlendirmektedir; bu nedenle, uzun vadeli bir i\u015f ak\u0131\u015f\u0131 olu\u015fturmadan \u00f6nce model listesini kontrol etmenizi \u00f6neririz.<\/span><\/p>\n<p><b>Llama 2<\/b><span style=\"font-weight: 400;\"> (Temmuz 2023\u2019te piyasaya s\u00fcr\u00fcld\u00fc) Meta\u2019n\u0131n \u015fu \u00f6zelliklere sahip modelidir: <\/span><a href=\"https:\/\/huggingface.co\/meta-llama\/Llama-2-7b\"><span style=\"font-weight: 400;\">available a\u011f\u0131rl\u0131klar\u0131<\/span><\/a><span style=\"font-weight: 400;\"> Meta\u2019n\u0131n lisans\u0131 kapsam\u0131nda kendi altyap\u0131n\u0131zda indirip \u00e7al\u0131\u015ft\u0131rabilece\u011finiz bir \u00e7\u00f6z\u00fcmd\u00fcr. Verileriniz \u00fczerinde kontrol sa\u011flar; kar\u015f\u0131l\u0131\u011f\u0131nda ise teknik uzmanl\u0131k ve donan\u0131m yat\u0131r\u0131m\u0131 gerektirir.<\/span><\/p>\n<p><b>Kar\u015f\u0131la\u015ft\u0131rma \u00d6zeti:<\/b><\/p>\n<p><b>GPT-5:<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u00c7\u0131k\u0131\u015f Tarihi: 7 A\u011fustos 2025<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Ba\u011flam Penceresi: 400.000 token<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Model T\u00fcr\u00fc: \u00d6zel\/Kapal\u0131<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Girdiler: Metin ve resim; \u00e7\u0131kt\u0131 olarak metin<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Da\u011f\u0131t\u0131m: API<\/span><\/li>\n<\/ul>\n<p><b>Llama 2:<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u00c7\u0131k\u0131\u015f Tarihi: Temmuz 2023<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Ba\u011flam Penceresi: 4.096 token<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Model T\u00fcr\u00fc: Lisansl\u0131 a\u011f\u0131rl\u0131klar available<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Giri\u015fler: Metin<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Da\u011f\u0131t\u0131m: Kendi sunucunuzda bar\u0131nd\u0131rma veya API<\/span><\/li>\n<\/ul>\n<h2><b>LLM Analizinde Yapay Zeka Transkripsiyon Yaz\u0131l\u0131m\u0131n\u0131n Rol\u00fc<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">\u0130\u015fte \u00e7o\u011fu ekibin g\u00f6zden ka\u00e7\u0131rd\u0131\u011f\u0131 ger\u00e7ek \u015fudur: Transkriptinizin kalitesi, LLM \u00e7\u0131kt\u0131n\u0131z\u0131n kalitesini do\u011frudan belirler. Modele da\u011f\u0131n\u0131k, hatalarla dolu bir metin girdi\u011finizde, da\u011f\u0131n\u0131k ve g\u00fcvenilmez bir analiz elde edersiniz.<\/span><\/p>\n<h3><b>Yapay Zeka Transkripsiyonu, B\u00fcy\u00fck Dil Modellerini Nas\u0131l Besliyor?<\/b><\/h3>\n<p><a href=\"https:\/\/sonix.ai\/transcription-software\"><span style=\"font-weight: 400;\">Yapay zeka transkripsiyon yaz\u0131l\u0131m\u0131<\/span><\/a><span style=\"font-weight: 400;\"> konu\u015fulan kelimeleri, b\u00fcy\u00fck dil modellerinin (LLM) i\u015fleyebilece\u011fi yap\u0131land\u0131r\u0131lm\u0131\u015f metne d\u00f6n\u00fc\u015ft\u00fcr\u00fcr. T\u00fcm transkripsiyonlar ayn\u0131 kalitede de\u011fildir. \u00d6nemli kalite fakt\u00f6rleri \u015funlard\u0131r:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Kelime do\u011frulu\u011fu:<\/b><span style=\"font-weight: 400;\"> Transkript, said\u2019de ger\u00e7ekte s\u00f6ylenenleri do\u011fru bir \u015fekilde yans\u0131t\u0131yor mu?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Konu\u015fmac\u0131 bilgisi:<\/b><span style=\"font-weight: 400;\"> said\u2019ye kimin ne s\u00f6yledi\u011fini s\u00f6yleyebilir misin?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Noktalama i\u015faretleri ve bi\u00e7imlendirme:<\/b><span style=\"font-weight: 400;\"> Metin d\u00fczg\u00fcn bir \u015fekilde yap\u0131land\u0131r\u0131lm\u0131\u015f m\u0131?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Zaman damgalar\u0131:<\/b><span style=\"font-weight: 400;\"> Orijinal kay\u0131ttaki belirli anlara at\u0131fta bulunabilir misiniz?<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Sonix, t\u00fcm bu fakt\u00f6rleri \u015fu \u015fekilde ele almaktad\u0131r:<\/span> <a href=\"https:\/\/sonix.ai\/features\/automated-transcription\"><span style=\"font-weight: 400;\">99%'ye kadar do\u011fruluk<\/span><\/a><span style=\"font-weight: 400;\"> Net ses kalitesi, otomatik konu\u015fmac\u0131 tan\u0131mlama ve kelime baz\u0131nda zaman damgalar\u0131 sayesinde, se\u00e7ti\u011finiz herhangi bir b\u00fcy\u00fck dil modeli (LLM) i\u00e7in temiz bir girdi olu\u015fturur. Do\u011fruluk, kay\u0131t ko\u015fullar\u0131na, konu\u015fmac\u0131lara, dile, aksanlara ve arka plan g\u00fcr\u00fclt\u00fcs\u00fcne g\u00f6re de\u011fi\u015fiklik g\u00f6sterir; bu nedenle, temiz bir kaynak ses elde etmek i\u00e7in kurulum zaman\u0131na harcad\u0131\u011f\u0131n\u0131z \u00e7abaya de\u011fer.<\/span><\/p>\n<h3><b>B\u00fcy\u00fck Dil Modelleri (LLM\u2019ler) \u0130\u00e7in Transkripsiyonlanm\u0131\u015f Ses Dosyalar\u0131n\u0131n Getirdi\u011fi Zorluklar<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Ara\u015ft\u0131rmalar, transkripsiyon hatalar\u0131n\u0131n b\u00fcy\u00fck dil modellerinin (LLM) performans\u0131 \u00fczerinde \u00f6l\u00e7\u00fclebilir olumsuz etkileri oldu\u011funu ortaya koymaktad\u0131r. Yap\u0131lan \u00e7al\u0131\u015fmalar, konu\u015fma tan\u0131ma hatalar\u0131n\u0131n sonraki a\u015famalardaki performans g\u00f6stergelerini \u00f6nemli \u00f6l\u00e7\u00fcde d\u00fc\u015f\u00fcrd\u00fc\u011f\u00fcn\u00fc ve fonetik a\u00e7\u0131dan \u00f6nemsiz hatalar\u0131n bile zararl\u0131 sonu\u00e7lar do\u011furdu\u011funu ortaya koymu\u015ftur.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">T\u0131bbi ortamlarda b\u00fcy\u00fck dil modellerinin (LLM) transkripsiyon do\u011frulu\u011funa ili\u015fkin bir ara\u015ft\u0131rma, az say\u0131da hatan\u0131n bile dok\u00fcmantasyon \u00fczerinde \u00f6nemli bir etkiye sahip olabilece\u011fini ortaya koydu; bu da, otonom not olu\u015fturma amac\u0131yla b\u00fcy\u00fck dil modellerini kullan\u0131rken dikkatli olunmas\u0131 gerekti\u011fini ortaya koyuyor.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Buradan \u00e7\u0131kar\u0131lacak ders a\u00e7\u0131k: \u00d6nce do\u011fru transkripsiyona yat\u0131r\u0131m yap\u0131n, ard\u0131ndan LLM yeteneklerini kullan\u0131n. Sonix\u2019in <\/span><a href=\"https:\/\/sonix.ai\/features\/ai-analysis\"><span style=\"font-weight: 400;\">Yapay zeka analiz \u00f6zellikleri<\/span><\/a><span style=\"font-weight: 400;\"> hatta harici modellere aktarmadan \u00f6nce ilk i\u00e7g\u00f6r\u00fc \u00e7\u0131kar\u0131m\u0131n\u0131 bile ger\u00e7ekle\u015ftirebilir.<\/span><\/p>\n<h2><b>Ger\u00e7ek D\u00fcnyadan Al\u0131nan Transkripsiyon Verileriyle B\u00fcy\u00fck Dil Modellerinin Performans\u0131n\u0131n Kar\u015f\u0131la\u015ft\u0131r\u0131lmas\u0131<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Transkript analizi a\u00e7\u0131s\u0131ndan GPT-5 ile Llama 2\u2019yi kar\u015f\u0131la\u015ft\u0131r\u0131rken, yay\u0131nlanm\u0131\u015f teknik \u00f6zellikler durumu net bir \u015fekilde ortaya koyuyor.<\/span><\/p>\n<h3><b>Kar\u015f\u0131la\u015ft\u0131rman\u0131n Haz\u0131rlanmas\u0131: Veri K\u00fcmeleri ve \u00d6l\u00e7\u00fctler<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Modeller, transkripsiyonlanm\u0131\u015f i\u00e7eri\u011fi i\u015fleme bi\u00e7imlerinde farkl\u0131l\u0131klar sergilemektedir:<\/span><\/p>\n<p><b>GPT-5:<\/b><span style=\"font-weight: 400;\"> OpenAI, GPT-5\u2019i matematiksel ak\u0131l y\u00fcr\u00fctme, yaz\u0131l\u0131m m\u00fchendisli\u011fi g\u00f6revleri ve \u00e7ok modlu anlama alanlar\u0131nda at\u0131lm\u0131\u015f bir ad\u0131m olarak konumland\u0131r\u0131yor; bu modelde metinle birlikte g\u00f6r\u00fcnt\u00fc anlama da m\u00fcmk\u00fcn. 400.000 tokenlik ba\u011flam penceresi, transkripsiyon \u00e7al\u0131\u015fmalar\u0131 i\u00e7in \u00f6ne \u00e7\u0131kan bir \u00f6zellik olarak \u00f6ne \u00e7\u0131k\u0131yor.<\/span><\/p>\n<p><b>Llama 2:<\/b><span style=\"font-weight: 400;\"> Meta\u2019n\u0131n Llama 2 makalesi, genel do\u011fruluk rakamlar\u0131 yerine test setine \u00f6zg\u00fc de\u011ferlendirmelerle, 5-shot MMLU\u2019da GPT-3.5\u2019e yak\u0131n bir performans sergiledi\u011fini bildiriyor. \u00d6zetleme veya s\u0131n\u0131fland\u0131rma sonu\u00e7lar\u0131, veri setine, model varyant\u0131na, istemlere, ince ayarlamaya ve de\u011ferlendirme y\u00f6ntemine b\u00fcy\u00fck \u00f6l\u00e7\u00fcde ba\u011fl\u0131d\u0131r; bu nedenle, Llama 2 i\u00e7in al\u0131nt\u0131lanan herhangi bir rakam\u0131, yaln\u0131zca belirli bir \u00e7al\u0131\u015fmaya ait olarak de\u011ferlendirin.<\/span><\/p>\n<h3><b>GPT-5 ve Llama 2\u2019yi Nesnel Olarak Nas\u0131l Kar\u015f\u0131la\u015ft\u0131rabiliriz?<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">\u00d6zellikle metin transkripsiyonu s\u00f6z konusu oldu\u011funda, en \u00f6nemli \u00fc\u00e7 fakt\u00f6r \u015funlard\u0131r:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Ba\u011flam i\u015fleme:<\/b><span style=\"font-weight: 400;\"> Model, transkriptinizin tamam\u0131n\u0131 tek seferde i\u015fleyebilir mi?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Ger\u00e7eklere uygunluk:<\/b><span style=\"font-weight: 400;\"> Model, i\u00e7erikle ilgili sanr\u0131lara kap\u0131l\u0131yor mu ya da i\u00e7eri\u011fi yanl\u0131\u015f m\u0131 aktar\u0131yor?<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>G\u00f6reve \u00f6zg\u00fc performans:<\/b><span style=\"font-weight: 400;\"> \u00d6zetleme, varl\u0131k \u00e7\u0131karma veya sorular\u0131 yan\u0131tlama konusunda ne kadar ba\u015far\u0131l\u0131?<\/span><\/li>\n<\/ol>\n<p><span style=\"font-weight: 400;\">Daha geni\u015f ba\u011flam pencerelerine sahip modeller, tek bir komutla daha uzun konu\u015fma metinlerini i\u015fleyebilir. Llama 2, konu\u015fma metinleri ba\u011flam penceresine s\u0131\u011fd\u0131\u011f\u0131nda standart NLP g\u00f6revlerinde iyi performans g\u00f6sterir.<\/span><\/p>\n<h2><b>GPT-5\u2019in Karma\u015f\u0131k Konu\u015fma Dilini \u0130\u015fleme Konusundaki G\u00fc\u00e7l\u00fc Y\u00f6nleri<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">GPT-5, \u00f6zellikle uzun ses kay\u0131tlar\u0131 olmak \u00fczere, transkripsiyonlu i\u00e7eriklerle \u00e7al\u0131\u015fan ekiplere \u00f6nemli avantajlar sunuyor.<\/span><\/p>\n<h3><b>Konu\u015fma Dinamiklerini Y\u00f6netme<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">400.000 tokenlik ba\u011flam penceresi, konu\u015fma metni analiziyle neler yap\u0131labilece\u011fini de\u011fi\u015ftiriyor. Tipik bir saatlik toplant\u0131 yakla\u015f\u0131k 10.000 kelime \u00fcretir; bu da kabaca 13.300 token'a denk gelir. Bu kabaca hesaplamaya g\u00f6re, bu b\u00fcy\u00fckl\u00fckteki bir ba\u011flam penceresi tek bir komutda saatlerce s\u00fcren toplant\u0131 i\u00e7eri\u011fini bar\u0131nd\u0131rabilir; ancak token yo\u011funlu\u011fu, transkript, konu\u015fmac\u0131 say\u0131s\u0131 ve bi\u00e7imlendirmeye g\u00f6re \u00f6nemli \u00f6l\u00e7\u00fcde de\u011fi\u015fiklik g\u00f6sterir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Bu, ekiplerin \u015funlar\u0131 yapmas\u0131n\u0131 sa\u011flar:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Ara\u015ft\u0131rma g\u00f6r\u00fc\u015fme dizisinin tamam\u0131n\u0131 par\u00e7alara ay\u0131rmadan analiz edin<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Birden fazla transkriptteki temalar\u0131 ayn\u0131 anda kar\u015f\u0131la\u015ft\u0131r\u0131n<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Uzun kay\u0131tlar boyunca konu\u015fmalar\u0131n nas\u0131l geli\u015fti\u011fini takip edin<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Karma\u015f\u0131k takip sorular\u0131 i\u00e7in Maintain tam ba\u011flam\u0131<\/span><\/li>\n<\/ul>\n<h3><b>Geli\u015fmi\u015f Anlamsal Anlama<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">GPT-5\u2019in \u00e7ok modlu deste\u011fi metnin \u00f6tesine uzan\u0131r. Video i\u00e7eri\u011fi \u00fczerinde \u00e7al\u0131\u015f\u0131yorsan\u0131z, transkripti, \u00e7\u0131kar\u0131lm\u0131\u015f slaytlar veya kareler gibi desteklenen g\u00f6rsel girdilerle birle\u015ftirebilirsiniz; bu, sunum kay\u0131tlar\u0131, videolar\u0131n transkripsiyonu ve g\u00f6rseller etraf\u0131nda olu\u015fturulan i\u00e7erikler i\u00e7in kullan\u0131\u015fl\u0131d\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Daha y\u00fcksek olgusal do\u011fruluk, GPT-5\u2019i hassasiyetin \u00f6nemli oldu\u011fu profesyonel ortamlar i\u00e7in de\u011ferli k\u0131lar. Hukuki ifade kay\u0131tlar\u0131, t\u0131bbi dikte kay\u0131tlar\u0131 ve mevzuata uygunluk kay\u0131tlar\u0131, hepsi g\u00fcvenilir bir analiz gerektirir.<\/span><\/p>\n<h2><b>Llama 2\u2019nin Transkripsiyon \u0130\u015f Ak\u0131\u015flar\u0131 i\u00e7in Verimlili\u011fi ve \u00d6zelle\u015ftirilebilirli\u011fi<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Llama 2, \u00f6zellikle \u00f6zelle\u015ftirme, gizlilik veya altyap\u0131 kontrol\u00fc konusunda \u00f6zel gereksinimleri olan kurulu\u015flar i\u00e7in \u00e7e\u015fitli avantajlar sunmaktad\u0131r.<\/span><\/p>\n<h3><b>Belirli Transkripsiyon \u0130htiya\u00e7lar\u0131 i\u00e7in Tailoring Llama 2<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Ayarlanabilir model a\u011f\u0131rl\u0131klar\u0131 sayesinde, Llama 2\u2019yi kendi \u00f6zel kelime da\u011farc\u0131\u011f\u0131n\u0131za g\u00f6re ince ayarlayabilirsiniz. Bu, a\u015fa\u011f\u0131daki durumlarda \u00f6nemlidir:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>T\u0131bbi uygulamalar<\/b><span style=\"font-weight: 400;\"> \u00f6zel terminoloji i\u00e7eren klinik notlar\u0131n yaz\u0131ya d\u00f6k\u00fclmesi<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Hukuk ekipleri<\/b><span style=\"font-weight: 400;\"> sekt\u00f6re \u00f6zg\u00fc terminolojiyi kullanarak ifade tutanaklar\u0131n\u0131 i\u015flemek<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Teknoloji \u015firketleri<\/b><span style=\"font-weight: 400;\"> \u00fcr\u00fcne \u00f6zg\u00fc terimlerle \u00e7al\u0131\u015fmak<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Sonix, bu i\u015f ak\u0131\u015f\u0131n\u0131 \u015fu yollarla desteklemektedir: <\/span><a href=\"https:\/\/sonix.ai\/features\"><span style=\"font-weight: 400;\">\u00f6zel s\u00f6zl\u00fck \u00f6zellikleri<\/span><\/a><span style=\"font-weight: 400;\"> \u00d6zel terimlerin transkripsiyon do\u011frulu\u011funu art\u0131ran ve \u00f6zelle\u015ftirilmi\u015f Llama 2 kurulumunuza daha temiz girdi sa\u011flayan \u00f6zellikler.<\/span><\/p>\n<h3><b>Da\u011f\u0131t\u0131m Esnekli\u011fi<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Llama 2\u2019nin kendi sunucusunda bar\u0131nd\u0131rma se\u00e7ene\u011fi, a\u015fa\u011f\u0131daki \u00f6zelliklere sahip kurulu\u015flar i\u00e7in cazip hale geliyor:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">S\u0131k\u0131 veri yerle\u015fim \u015fartlar\u0131<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Y\u00fcksek hacimli i\u015fleme ihtiya\u00e7lar\u0131<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Mevcut makine \u00f6\u011frenimi altyap\u0131s\u0131<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u00d6zel entegrasyon gereksinimleri<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">D\u00fczenli olarak b\u00fcy\u00fck hacimli transkript i\u00e7eri\u011fini i\u015fleyen kurulu\u015flar i\u00e7in, kendi sunucular\u0131nda bar\u0131nd\u0131r\u0131lan kurulum, altyap\u0131 kontrol\u00fc sa\u011flar.<\/span><\/p>\n<h2><b>Pratik Uygulamalar: Transkripsiyonlanm\u0131\u015f R\u00f6portajlar ve Toplant\u0131larda B\u00fcy\u00fck Dil Modellerinin Kullan\u0131m\u0131<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Teoriyi anlamak faydal\u0131d\u0131r, ancak \u015fimdi pratik i\u015f ak\u0131\u015flar\u0131na bir g\u00f6z atal\u0131m.<\/span><\/p>\n<h3><b>Uzun Konu\u015fmalar\u0131 \u00d6zetleme<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Tipik bir kullan\u0131m \u00f6rne\u011fi olarak, bir saatlik bir toplant\u0131y\u0131 \u00f6zetlemek:<\/span><\/p>\n<p><b>GPT-5 ile:<\/b><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Sonix'e ses dosyas\u0131n\u0131 y\u00fcklemek i\u00e7in<\/span> <a href=\"https:\/\/sonix.ai\/fast-transcription\"><span style=\"font-weight: 400;\">h\u0131zl\u0131 transkripsiyon<\/span><\/a><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Konu\u015fmac\u0131 etiketleri i\u00e7eren bi\u00e7imlendirilmi\u015f transkripti d\u0131\u015fa aktar<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Transkriptin tamam\u0131n\u0131 tek bir komut sat\u0131r\u0131nda g\u00f6nderin<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Eylem maddelerini i\u00e7eren kapsaml\u0131 bir \u00f6zet al\u0131n<\/span><\/li>\n<\/ol>\n<p><b>Llama 2 ile:<\/b><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Transkripsiyon i\u00e7in ses dosyas\u0131n\u0131 Sonix\u2019e y\u00fckleyin<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Transkripti, ba\u011flam penceresine s\u0131\u011facak \u015fekilde par\u00e7alara b\u00f6l\u00fcnm\u00fc\u015f olarak d\u0131\u015fa aktar\u0131n<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Her bir b\u00f6l\u00fcm\u00fc s\u0131rayla i\u015fleyin<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Sonu\u00e7lar\u0131 birle\u015ftirin ve ba\u011flam\u0131n s\u00fcreklili\u011fini sa\u011flamak i\u00e7in bir mutabakat a\u015famas\u0131 ekleyin<\/span><\/li>\n<\/ol>\n<p><span style=\"font-weight: 400;\">Yakla\u015f\u0131k 20 dakikadan uzun ses kay\u0131tlar\u0131nda, daha geni\u015f ba\u011flam pencereleri, konu\u015fma tutarl\u0131l\u0131\u011f\u0131n\u0131 sa\u011flamada avantajlar sunar.<\/span><\/p>\n<h3><b>Ara\u015ft\u0131rmalardan \u00d6nemli Bulgular\u0131n \u00c7\u0131kar\u0131lmas\u0131<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Nitel ara\u015ft\u0131rmac\u0131lar, transkript hacmi konusunda belirli zorluklarla kar\u015f\u0131 kar\u015f\u0131yad\u0131r. Tipik bir ara\u015ft\u0131rma \u00e7al\u0131\u015fmas\u0131, 20 saatten fazla g\u00f6r\u00fc\u015fme kayd\u0131 \u00fcretebilir.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Sonix'in<\/span> <a href=\"https:\/\/sonix.ai\/features\/ai-analysis\"><span style=\"font-weight: 400;\">Yapay zeka analiz ara\u00e7lar\u0131<\/span><\/a><span style=\"font-weight: 400;\"> Harici bir LLM'ye gerek kalmadan temalar\u0131, konular\u0131 ve \u00f6nemli anlar\u0131 do\u011frudan \u00e7\u0131karabilir. Daha derinlemesine bir analiz i\u00e7in, transkriptleri tercih etti\u011finiz LLM'ye aktararak \u015funlar\u0131 yapabilirsiniz:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Birden fazla g\u00f6r\u00fc\u015fmede ortak kal\u0131plar\u0131 belirlemek<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Tematik kodlar\u0131 otomatik olarak olu\u015ftur<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Kat\u0131l\u0131mc\u0131lar aras\u0131nda \u00e7eli\u015fkiler veya tutarl\u0131l\u0131klar bulun<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Payda\u015flar i\u00e7in \u00f6zet raporlar haz\u0131rlay\u0131n<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Ara\u015ft\u0131rma, hukuk, medya ve kurumsal ekipler de kopyala-yap\u0131\u015ft\u0131r ad\u0131m\u0131n\u0131 tamamen atlayabilir. Sonix\u2019in MCP sunucusu, yapay zeka asistanlar\u0131n\u0131n Sonix k\u00fct\u00fcphanenizle g\u00fcvenli bir \u015fekilde \u00e7al\u0131\u015fmas\u0131na olanak tan\u0131r. G\u00fcn\u00fcm\u00fczde, ba\u011fl\u0131 asistanlar, salt okunur bir OAuth ba\u011flant\u0131s\u0131 arac\u0131l\u0131\u011f\u0131yla kay\u0131tlar\u0131 tarayabilir, transkriptleri ba\u011flam i\u00e7ine yerle\u015ftirebilir, transkript veya altyaz\u0131 d\u0131\u015fa aktar\u0131mlar\u0131 olu\u015fturabilir ve hesap durumunu kontrol edebilir. Bu salt okunur tasar\u0131m, d\u00fczenlemelere tabi ekipler i\u00e7in bir \u00f6zelliktir: asistanlar, kaynak materyali de\u011fi\u015ftirme olana\u011f\u0131 olmadan mevcut transkriptleri analiz eder.<\/span><\/p>\n<h3><b>Ba\u011flant\u0131l\u0131 Asistanlar Arac\u0131l\u0131\u011f\u0131yla Yapay Zeka Analizi Yapmak<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Sonix k\u00fct\u00fcphaneniz MCP \u00fczerinden ba\u011fland\u0131ktan sonra, bir asistan straight transkriptini ba\u011flam i\u00e7ine yerle\u015ftirebilir ve ara\u015ft\u0131rmac\u0131lar ile medya ekiplerinin halihaz\u0131rda manuel olarak ger\u00e7ekle\u015ftirdi\u011fi analiz ad\u0131mlar\u0131n\u0131 uygulayabilir:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Tam bir r\u00f6portaj metni \u00fczerinden soru-cevap<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Uzun toplant\u0131lar\u0131n, panellerin ve ifade al\u0131mlar\u0131n\u0131n \u00f6zetleri<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Kat\u0131l\u0131mc\u0131lar veya oturumlar genelinde duygu analizi<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u0130simler, kurulu\u015flar, \u00fcr\u00fcnler ve tarihler i\u00e7in varl\u0131k \u00e7\u0131karma<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Bir dizi ilgili kay\u0131ttan i\u00e7g\u00f6r\u00fc \u00e7\u0131kar\u0131m\u0131<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Uyumlu istemciler aras\u0131nda Claude Code, Claude Desktop, Cursor, Codex, Windsurf, VS Code ve di\u011fer MCP uyumlu ara\u00e7lar yer almaktad\u0131r. \u0130stemcinizi \u015fu adrese y\u00f6nlendirin: <\/span><span style=\"font-weight: 400;\">https:\/\/api.sonix.ai\/mcp<\/span><span style=\"font-weight: 400;\"> ve g\u00fcvenli OAuth oturum a\u00e7ma i\u015flemini tamamlay\u0131n. Kurulum, otomatik ke\u015fif ve kay\u0131t \u00f6zelli\u011fini kullan\u0131r; bu nedenle yap\u0131\u015ft\u0131rman\u0131z gereken herhangi bir API anahtar\u0131 yoktur ve eri\u015fimi istedi\u011finiz zaman iptal edebilirsiniz. MCP eri\u015fimi, paid planlar\u0131nda kullan\u0131labilir ve yaln\u0131zca hesap sahipleri ile \u00fcreticiler bir ba\u011flant\u0131y\u0131 yetkilendirebilir. Deneme ve \u00fccretsiz hesaplar ile \u00fcye d\u00fczeyindeki kullan\u0131c\u0131lar ise bunun yerine di\u011fer Sonix aray\u00fczleri \u00fczerinden ba\u011flanabilir.<\/span><\/p>\n<h3><b>Terminal'den Transkript \u0130\u015f Ak\u0131\u015flar\u0131n\u0131 Otomatikle\u015ftirme<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Geli\u015ftiriciler ve ileri d\u00fczey kullan\u0131c\u0131lar i\u00e7in Sonix CLI, Sonix i\u015f ak\u0131\u015f\u0131n\u0131 terminale ve CI boru hatlar\u0131na ta\u015f\u0131r. Salt okunur MCP sunucusunun aksine, CLI, Sonix REST API\u2019si \u00fczerinden metin d\u00f6n\u00fc\u015ft\u00fcrme, \u00e7eviri, altyaz\u0131 ekleme, \u00f6zetleme i\u015flemlerinin yan\u0131 s\u0131ra medya, klas\u00f6rler, kullan\u0131c\u0131lar ve payla\u015f\u0131mlar\u0131n y\u00f6netimi i\u00e7in bir otomasyon aray\u00fcz\u00fcd\u00fcr.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Tipik CLI ve API i\u015f ak\u0131\u015flar\u0131 \u015funlard\u0131r:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Planlanm\u0131\u015f bir i\u015f kapsam\u0131nda medya dosyalar\u0131n\u0131 transkripsiyonuna ve \u00e7evirisine<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Video i\u015f ak\u0131\u015flar\u0131 i\u00e7in altyaz\u0131 olu\u015fturma ve altyaz\u0131lar\u0131 videoya sabitleme<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Dosyalar\u0131 y\u00fcklemeden sonra otomatik olarak \u00f6zetle<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Medya dosyalar\u0131n\u0131, klas\u00f6rleri, kullan\u0131c\u0131lar\u0131 ve payla\u015f\u0131mlar\u0131 geni\u015f \u00f6l\u00e7ekte y\u00f6netin<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Depoya yeni kay\u0131tlar geldi\u011finde CI'dan transkripsiyon i\u015flemini ba\u015flat<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Bu <\/span><a href=\"https:\/\/sonix.ai\/api\"><span style=\"font-weight: 400;\">Sonix API'si<\/span><\/a><span style=\"font-weight: 400;\"> Kendi entegrasyonlar\u0131n\u0131 geli\u015ftiren ekipler i\u00e7in CLI\u2019nin alt\u0131nda yer al\u0131r. Sonix sitesindeki ba\u015flatma k\u0131lavuzunu kullanarak Sonix komut sat\u0131r\u0131 arac\u0131n\u0131 y\u00fckleyin.<\/span><\/p>\n<h2><b>LLM ile \u0130\u015flenmi\u015f Transkriptlerle Eri\u015filebilirli\u011fi ve Bulunabilirli\u011fi Art\u0131rma<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Analizin \u00f6tesinde, b\u00fcy\u00fck dil modelleri (LLM\u2019ler), transkripsiyonlanm\u0131\u015f i\u00e7eri\u011fin daha geni\u015f kitlelere ula\u015fma \u015feklini iyile\u015ftirebilir.<\/span><\/p>\n<h3><b>LLM \u0130yile\u015ftirmesi ile Otomatik Altyaz\u0131 Olu\u015fturma<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Sonix'in <\/span><a href=\"https:\/\/sonix.ai\/features\/automated-subtitles\"><span style=\"font-weight: 400;\">otomatik altyaz\u0131lar<\/span><\/a><span style=\"font-weight: 400;\"> transkripsiyonlardan do\u011frudan SRT ve VTT dosyalar\u0131 olu\u015fturmak. B\u00fcy\u00fck Dil Modelleri (LLM'ler) daha sonra \u015funlar\u0131 yapabilir:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Altyaz\u0131 zamanlamas\u0131n\u0131 ve sat\u0131r sonlar\u0131n\u0131 iyile\u015ftirin<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Farkl\u0131 hedef kitle gruplar\u0131na g\u00f6re \u00fcslubu uyarlay\u0131n<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Farkl\u0131 okuma seviyelerine y\u00f6nelik alternatif ba\u015fl\u0131k metinleri tasla\u011f\u0131<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Sesli a\u00e7\u0131klamal\u0131 SDH (\u0130\u015fitme Engelliler ve \u0130\u015fitme G\u00fc\u00e7l\u00fc\u011f\u00fc \u00c7ekenler i\u00e7in Altyaz\u0131lar) olu\u015fturun<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Bu i\u015f ak\u0131\u015f\u0131, i\u00e7eri\u011fin eri\u015fim alan\u0131n\u0131 geni\u015fletirken eri\u015filebilirlik kurallar\u0131na uyumu da destekler.<\/span><\/p>\n<h3><b>Transkriptler Arac\u0131l\u0131\u011f\u0131yla \u0130\u00e7erik Eri\u015fiminin Art\u0131r\u0131lmas\u0131<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Arama motorlar\u0131 ses dosyalar\u0131n\u0131 indeksleyemez, ancak transkriptleri indeksleyebilir. Transkripsiyonlanm\u0131\u015f i\u00e7eri\u011fi yay\u0131nlamak, hem SEO\u2019yu hem de eri\u015filebilirli\u011fi ayn\u0131 anda iyile\u015ftirir. Sonix\u2019in <\/span><a href=\"https:\/\/sonix.ai\/seo-friendly-media-player\"><span style=\"font-weight: 400;\">medya oynat\u0131c\u0131<\/span><\/a><span style=\"font-weight: 400;\"> videonun yan\u0131na altyaz\u0131lar\u0131 ekleyerek i\u00e7eri\u011fin bulunabilirli\u011fini art\u0131r\u0131rken, ADA gerekliliklerini de destekler.<\/span><\/p>\n<h2><b>Transkripsiyon \u0130htiya\u00e7lar\u0131n\u0131za Uygun Do\u011fru LLM\u2019yi Se\u00e7mek<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Do\u011fru se\u00e7im, sizin \u00f6zel durumunuza ba\u011fl\u0131d\u0131r. \u0130\u015fte bir karar verme \u00e7er\u00e7evesi:<\/span><\/p>\n<h3><b>GPT-5'i Ne Zaman Se\u00e7melisiniz?<\/b><\/h3>\n<p><b>A\u015fa\u011f\u0131daki durumlarda GPT-5'i de\u011ferlendirin:<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">20 dakikadan uzun transkriptlerin b\u00f6l\u00fcmlere ayr\u0131lmadan analizi<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Hukuk, t\u0131p veya mevzuata uygunluk alanlar\u0131ndaki i\u00e7erikler i\u00e7in y\u00fcksek do\u011fruluk<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Transkriptleri desteklenen g\u00f6r\u00fcnt\u00fc girdileriyle birle\u015ftiren \u00e7ok modlu analiz<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Asgari kurulum ve an\u0131nda devreye alma<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Birden fazla kayd\u0131 kapsayan \u00e7apraz transkript analizi<\/span><\/li>\n<\/ul>\n<p><b>\u0130deal kullan\u0131m \u00f6rnekleri:<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Yasal ifade analizi<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">T\u0131bbi belgelerin incelenmesi<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Kurumsal toplant\u0131 analiti\u011fi<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Akademik ara\u015ft\u0131rma \u00f6zeti<\/span><\/li>\n<\/ul>\n<h3><b>Llama 2'yi Ne Zaman Se\u00e7melisiniz?<\/b><\/h3>\n<p><b>A\u015fa\u011f\u0131daki durumlarda Llama 2'yi se\u00e7in:<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u015eirket i\u00e7i kurulum ile tam veri gizlili\u011fi<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u00d6zel kelime da\u011farc\u0131\u011f\u0131 i\u00e7in \u00f6zel ince ayar<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Model davran\u0131\u015flar\u0131 ve g\u00fcncellemeler \u00fczerinde tam kontrol<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Mevcut makine \u00f6\u011frenimi altyap\u0131s\u0131ndan yararlanmak<\/span><\/li>\n<\/ul>\n<p><b>\u0130deal kullan\u0131m \u00f6rnekleri:<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">HIPAA gerekliliklerine tabi sa\u011fl\u0131k kurulu\u015flar\u0131<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Veri egemenli\u011fi ihtiyac\u0131 olan devlet kurumlar\u0131<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u00d6zel terminolojiye sahip kurulu\u015flar<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Makine \u00f6\u011frenimi altyap\u0131s\u0131na sahip teknik ekipler<\/span><\/li>\n<\/ul>\n<h3><b>Transkripsiyon Kalitesi Neden Her \u0130kisi \u0130\u00e7in de \u00d6nemlidir?<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Hangi LLM\u2019yi se\u00e7erseniz se\u00e7in, transkripsiyon kalitesi temelinizdir. Sonix bunu sa\u011flar <\/span><a href=\"https:\/\/sonix.ai\/features\/automated-transcription\"><span style=\"font-weight: 400;\">99%'ye kadar do\u011fruluk<\/span><\/a><span style=\"font-weight: 400;\"> net ses kalitesinde ve \u015funlar\u0131 destekler: <\/span><a href=\"https:\/\/sonix.ai\/languages\"><span style=\"font-weight: 400;\">54'ten fazla dil<\/span><\/a><span style=\"font-weight: 400;\">, her iki modele de temiz girdi sa\u011flar. Sonix\u2019in <\/span><a href=\"https:\/\/sonix.ai\/security\"><span style=\"font-weight: 400;\">SOC 2 uyumlulu\u011fu<\/span><\/a><span style=\"font-weight: 400;\"> \u0130ster bulut tabanl\u0131 b\u00fcy\u00fck dil modellerini (LLM\u2019ler) ister kendi sunucular\u0131n\u0131zda bar\u0131nd\u0131r\u0131lan se\u00e7enekleri kullan\u0131yor olun, kurumsal d\u00fczeyde g\u00fcvenlik sa\u011flar.<\/span><\/p>\n<h2><b>Sonix\u2019in Avantaj\u0131: Ba\u015far\u0131l\u0131 LLM Analizinin Temeli<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">GPT-5, Llama 2 veya ba\u015fka herhangi bir dil modeli aras\u0131nda se\u00e7im yapmadan \u00f6nce, bu modellerin ger\u00e7ekten i\u015fleyebilece\u011fi transkriptlere ihtiyac\u0131n\u0131z vard\u0131r. \u0130\u015fte bu noktada Sonix, i\u015f ak\u0131\u015f\u0131n\u0131z i\u00e7in vazge\u00e7ilmez hale gelir.<\/span><\/p>\n<p><b>Sonix Neden LLM\u2019nizin En \u0130yi Arkada\u015f\u0131d\u0131r:<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>\u00d6nemli olan do\u011fruluk:<\/b><span style=\"font-weight: 400;\"> ile <\/span><a href=\"https:\/\/sonix.ai\/features\/automated-transcription\"><span style=\"font-weight: 400;\">99%'ye kadar do\u011fruluk<\/span><\/a><span style=\"font-weight: 400;\"> Net bir ses kayd\u0131nda Sonix, se\u00e7ti\u011finiz b\u00fcy\u00fck dil modeline (LLM) hatas\u0131z ve g\u00fcvenilir bir metin sa\u011flar. \u0130ster GPT-5 \u00fczerinden ister ince ayarlanm\u0131\u015f bir a\u00e7\u0131k kaynakl\u0131 model \u00fczerinden analiz yap\u0131yor olun, do\u011fru bir transkripsiyonla ba\u015flamak, en g\u00fc\u00e7l\u00fc yapay zeka sistemlerini bile zay\u0131flatan \u201c\u00e7\u00f6p girerse \u00e7\u00f6p \u00e7\u0131kar\u201d sorununu azalt\u0131r.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Yerle\u015fik zeka:<\/b><span style=\"font-weight: 400;\"> Sonix sadece metne d\u00f6n\u00fc\u015ft\u00fcrmekle kalmaz, ayn\u0131 zamanda analiz de yapar. Sonix\u2019in <\/span><a href=\"https:\/\/sonix.ai\/features\/ai-analysis\"><span style=\"font-weight: 400;\">Yapay zeka analiz \u00f6zellikleri<\/span><\/a><span style=\"font-weight: 400;\"> otomatik \u00f6zetler, ana temalar, konu alg\u0131lama, duygu analizi ve varl\u0131k \u00e7\u0131karma gibi anl\u0131k i\u00e7g\u00f6r\u00fcler sunar. Bir\u00e7ok i\u015f ak\u0131\u015f\u0131nda, harici bir LLM\u2019ye aktar\u0131m yapmaya hi\u00e7 gerek kalmadan ihtiyac\u0131n\u0131z olan i\u00e7g\u00f6r\u00fclere ula\u015fabilirsiniz.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Sorunsuz entegrasyon:<\/b><span style=\"font-weight: 400;\"> D\u0131\u015f LLM yeteneklerine ihtiya\u00e7 duydu\u011funuzda, Sonix entegrasyonu son derece kolay hale getirir. Konu\u015fmac\u0131 etiketleri ve zaman damgalar\u0131 i\u00e7eren, temiz ve bi\u00e7imlendirilmi\u015f transkriptleri DOCX, TXT, PDF, SRT, VTT ve JSON formatlar\u0131nda d\u0131\u015fa aktar\u0131n. Transkriptleriniz, ba\u011flam\u0131 korunmu\u015f ve konu\u015fmac\u0131lar tan\u0131mlanm\u0131\u015f \u015fekilde d\u00fczg\u00fcn bir yap\u0131ya sahip olarak size ula\u015f\u0131r; bu da dil modellerinin do\u011fru analiz yapabilmesi i\u00e7in tam olarak ihtiya\u00e7 duydu\u011fu \u015feydir.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Kurumsal d\u00fczeyde g\u00fcvenlik:<\/b><span style=\"font-weight: 400;\"> SOC 2 Tip II uyumlulu\u011fu, depolama ve aktar\u0131m s\u0131ras\u0131nda \u015fifreleme, SSO ve SAML deste\u011fi ile kapsaml\u0131 eri\u015fim denetimleri sayesinde Sonix, verilerinizi ister bulut API\u2019lerine ister kendi sunucular\u0131n\u0131zda bar\u0131nd\u0131r\u0131lan modellere y\u00f6nlendiriyor olun, her durumda korur. HIPAA uyumlu i\u015f ak\u0131\u015flar\u0131, BAA anla\u015fmas\u0131 kapsam\u0131nda Medical Sonix arac\u0131l\u0131\u011f\u0131yla kullan\u0131labilir.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>K\u00fcresel dil deste\u011fi:<\/b><span style=\"font-weight: 400;\"> Sonix, a\u015fa\u011f\u0131dakilerde otomatik transkripsiyonu destekler: <\/span><a href=\"https:\/\/sonix.ai\/languages\"><span style=\"font-weight: 400;\">54'ten fazla dil<\/span><\/a><span style=\"font-weight: 400;\">, d\u00fcnya \u00e7ap\u0131nda da\u011f\u0131lm\u0131\u015f ekipler i\u00e7in \u00e7ok dilli transkripsiyon i\u015f ak\u0131\u015flar\u0131n\u0131 ve b\u00fcy\u00fck dil modelleri (LLM) ile uyumlu bi\u00e7imlendirmeyi m\u00fcmk\u00fcn k\u0131lar.<\/span><\/li>\n<\/ul>\n<p><b>Sonix art\u0131k zaten \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131z ortamlarda da hizmetinizde: MCP ile yapay zeka asistan\u0131n\u0131z\u0131n i\u00e7inde ve CLI ile terminalinizde.<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Sonix, yeni nesil yapay zeka ve geli\u015ftirici i\u015f ak\u0131\u015flar\u0131na da uyum sa\u011flar. MCP sunucusu, Claude Code, Claude Desktop, Cursor, Codex, Windsurf ve VS Code gibi uyumlu yapay zeka asistanlar\u0131n\u0131n, g\u00fcvenli bir OAuth ba\u011flant\u0131s\u0131 arac\u0131l\u0131\u011f\u0131yla Sonix k\u00fct\u00fcphanenizle do\u011frudan \u00e7al\u0131\u015fmas\u0131n\u0131 sa\u011flar. \u0130stemcinizi \u015fu adrese y\u00f6nlendirin: <\/span><span style=\"font-weight: 400;\">https:\/\/api.sonix.ai\/mcp<\/span><span style=\"font-weight: 400;\">, oturum a\u00e7\u0131n; asistan\u0131n\u0131z kay\u0131tlar\u0131 inceleyebilir, \u00f6zetleme veya soru-cevap ama\u00e7l\u0131 olarak transkriptleri ba\u011flam i\u00e7ine yerle\u015ftirebilir ve temiz transkript veya altyaz\u0131 dosyalar\u0131n\u0131 TXT, SRT, VTT ve JSON formatlar\u0131nda d\u0131\u015fa aktarabilir. MCP \u015fu anda salt okunur durumdad\u0131r; bu, dosya olu\u015fturmak veya d\u00fczenlemek yerine mevcut medya ve transkriptlere g\u00fcvenli eri\u015fim sa\u011flamak \u00fczere tasarland\u0131\u011f\u0131 anlam\u0131na gelir. Yazma ara\u00e7lar\u0131 ise yol haritas\u0131nda yer almaktad\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Geli\u015ftiriciler ve operasyon ekipleri i\u00e7in Sonix CLI, otomasyon s\u00fcrecini \u00fcstlenir. Sonix REST API\u2019si \u00fczerinden transkripsiyon, \u00e7eviri, altyaz\u0131 olu\u015fturma, sabit altyaz\u0131lar, \u00f6zetler ve medya y\u00f6netimini terminal ve CI i\u015f ak\u0131\u015flar\u0131na entegre eder.<\/span><\/p>\n<p><b>Sonu\u00e7 olarak:<\/b><span style=\"font-weight: 400;\"> GPT-5 ve Llama 2, dil modeli da\u011f\u0131t\u0131m\u0131na y\u00f6nelik farkl\u0131 yakla\u015f\u0131mlar\u0131 temsil eder ve her ikisinin de kendine \u00f6zg\u00fc avantajlar\u0131 vard\u0131r. Hi\u00e7bir model, d\u00fc\u015f\u00fck transkripsiyon kalitesini telafi edemez. Sonix ile ba\u015flayarak, hangi b\u00fcy\u00fck dil modeli (LLM) yolunu se\u00e7erseniz se\u00e7in, analizinizin do\u011fruluk temeli \u00fczerine in\u015fa edildi\u011finden emin olabilirsiniz. Sonix, Google, Adobe, Stanford ve ESPN\u2019deki ekipler taraf\u0131ndan g\u00fcvenilmektedir.<\/span><\/p>\n<h2><b>Sonu\u00e7: Ba\u011flam Pencereleri, \u00d6zelle\u015ftirme ve Transkripsiyon Temeli<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">GPT-5 ile Llama 2 aras\u0131nda yap\u0131lacak se\u00e7im, nihayetinde sizin \u00f6zel gereksinimlerinize ba\u011fl\u0131d\u0131r:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>A\u015fa\u011f\u0131dakileri \u00f6ncelikli g\u00f6r\u00fcyorsan\u0131z GPT-5'i se\u00e7in:<\/b><span style=\"font-weight: 400;\"> Uzun transkriptleri u\u00e7tan uca i\u015flemek i\u00e7in 400.000 tokenlik bir ba\u011flam penceresi, g\u00fc\u00e7l\u00fc ak\u0131l y\u00fcr\u00fctme performans\u0131, asgari altyap\u0131 gereksinimleri ve transkriptleri desteklenen g\u00f6r\u00fcnt\u00fc girdileriyle birle\u015ftiren \u00e7ok modlu analiz. Yeni projeler i\u00e7in art\u0131k daha yeni GPT-5.x s\u00fcr\u00fcmlerinin \u00f6nerildi\u011fini g\u00f6z \u00f6n\u00fcnde bulundurarak, \u00f6ncelikle OpenAI\u2019nin g\u00fcncel model listesine g\u00f6z at\u0131n.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>A\u015fa\u011f\u0131dakileri \u00f6ncelikli g\u00f6r\u00fcyorsan\u0131z Llama 2'yi se\u00e7in:<\/b><span style=\"font-weight: 400;\"> Kendi sunucular\u0131nda bar\u0131nd\u0131rma yoluyla tam veri kontrol\u00fc, \u00f6zel domains ve kelime da\u011farc\u0131\u011f\u0131na g\u00f6re ince ayar yapma imkan\u0131, altyap\u0131 esnekli\u011fi ve belirli kullan\u0131m senaryolar\u0131na g\u00f6re model davran\u0131\u015f\u0131n\u0131n \u00f6zelle\u015ftirilmesi.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Hangi modeli se\u00e7erseniz se\u00e7in,<\/b><span style=\"font-weight: 400;\"> Transkripsiyon kalitesi, ba\u015far\u0131n\u0131z\u0131 belirler. \u0130ster bulut tabanl\u0131 ister kendi sunucunuzda bar\u0131nd\u0131r\u0131lan, ister \u00f6zel yaz\u0131l\u0131m ister a\u00e7\u0131k kaynak olsun, her iki yakla\u015f\u0131m da girdi olarak do\u011fru transkriptlere dayan\u0131r.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Sonix, bu hayati temeli \u015fu \u00f6zelliklerle sa\u011flar: <\/span><a href=\"https:\/\/sonix.ai\/features\/automated-transcription\"><span style=\"font-weight: 400;\">99%'ye kadar do\u011fruluk<\/span><\/a><span style=\"font-weight: 400;\"> net ses \u00fczerinde,<\/span> <a href=\"https:\/\/sonix.ai\/features\/automated-transcription\"><span style=\"font-weight: 400;\">otomati\u0307k transkri\u0307psi\u0307yon<\/span><\/a><span style=\"font-weight: 400;\"> 54'ten fazla dilde destek, yerle\u015fik yapay zeka analizi, kurumsal d\u00fczeyde g\u00fcvenlik ve art\u0131k MCP arac\u0131l\u0131\u011f\u0131yla yapay zeka asistanlar\u0131na ve CLI arac\u0131l\u0131\u011f\u0131yla terminal i\u015f ak\u0131\u015flar\u0131na do\u011frudan ba\u011flant\u0131. \u0130\u015f ak\u0131\u015f\u0131n\u0131za en uygun LLM i\u00e7in haz\u0131r, temiz ve d\u00fczg\u00fcn bi\u00e7imlendirilmi\u015f transkriptlere sahip olursunuz; ayr\u0131ca, harici modelleri hi\u00e7 kullanmadan \u00f6nce do\u011frudan Sonix i\u00e7inde i\u00e7g\u00f6r\u00fcler elde etme se\u00e7ene\u011finiz de vard\u0131r.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">D\u00fcnyan\u0131n en g\u00fc\u00e7l\u00fc dil modeli bile hatal\u0131 bir transkripti d\u00fczeltemez. Sonix ile ba\u015flay\u0131n, ard\u0131ndan teknik ve i\u015f gereksinimlerinize uygun LLM\u2019yi se\u00e7in.<\/span><\/p>\n<h2><b>Sonraki Ad\u0131mlar<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Bir kayd\u0131 y\u00fckleyin, dilinizi se\u00e7in ve modelinizin bekledi\u011fi formatta konu\u015fmac\u0131 etiketli bir transkripti d\u0131\u015fa aktar\u0131n. Ard\u0131ndan, mevcut transkriptlerin salt okunur analizini yapmak i\u00e7in AI asistan\u0131n\u0131z\u0131 MCP \u00fczerinden ba\u011flay\u0131n ya da senaryo tabanl\u0131 transkripsiyon, \u00e7eviri, altyaz\u0131 ve \u00f6zetleme i\u015flemleri i\u00e7in Sonix CLI\u2019yi i\u015f ak\u0131\u015f\u0131n\u0131za entegre edin.<\/span><\/p>\n<p><a href=\"https:\/\/sonix.ai\/accounts\/sign_up\"><span style=\"font-weight: 400;\">Sonix\u2019i \u00fccretsiz deneyin<\/span><\/a><span style=\"font-weight: 400;\">: 30 dakika, kredi kart\u0131 gerekmez.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Ke\u015ffedin <\/span><a href=\"https:\/\/sonix.ai\/features\"><span style=\"font-weight: 400;\">Sonix\u2019in \u00f6zellikleri<\/span><\/a><span style=\"font-weight: 400;\">, yapay zeka analizi, otomatik altyaz\u0131lar ve ekibinizin halihaz\u0131rda kulland\u0131\u011f\u0131 ara\u00e7larla entegrasyonlar da dahil olmak \u00fczere.<\/span><\/p>\n<h2><b>S\u0131k\u00e7a Sorulan Sorular<\/b><\/h2>\n<h3><b>Transkripsiyonlu metin analizi a\u00e7\u0131s\u0131ndan GPT-5 ile Llama 2 aras\u0131ndaki main fark\u0131 nedir?<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">En b\u00fcy\u00fck pratik fark, ba\u011flam penceresinin boyutudur. GPT-5, 400.000 tokenlik bir ba\u011flam penceresini destekler; bu, tek bir komutla saatlerce s\u00fcren ses kayd\u0131n\u0131n transkripsiyonu i\u00e7in yeterlidir, ancak kesin miktar transkript yo\u011funlu\u011funa g\u00f6re de\u011fi\u015fiklik g\u00f6sterir. Orijinal Llama 2 modelleri 4.096 tokenlik bir ba\u011flam penceresi kullan\u0131r; bu nedenle, yakla\u015f\u0131k 15 ila 20 dakikay\u0131 a\u015fan transkriptlerin b\u00f6l\u00fcmlere ayr\u0131lmas\u0131 gerekir. Daha b\u00fcy\u00fck ba\u011flam pencereleri, uzun kay\u0131tlar boyunca tam bir konu\u015fma ba\u011flam\u0131 sa\u011flarken, daha k\u00fc\u00e7\u00fck pencereler ise \u00f6nceki ve sonraki b\u00f6l\u00fcmler aras\u0131ndaki ba\u011flant\u0131lar\u0131 korumak i\u00e7in par\u00e7alama stratejinize ba\u011fl\u0131d\u0131r.<\/span><\/p>\n<h3><b>LLM\u2019leri kullan\u0131rken transkripsiyon do\u011frulu\u011fu ne kadar \u00f6nemlidir?<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Kritik \u00f6nemde. Ara\u015ft\u0131rmalar, konu\u015fma-metin d\u00f6n\u00fc\u015ft\u00fcrme hatalar\u0131n\u0131n \u00f6zetleme, varl\u0131k \u00e7\u0131karma ve analiz g\u00f6revlerinde b\u00fcy\u00fck dil modellerinin (LLM) performans\u0131n\u0131 d\u00fc\u015f\u00fcrd\u00fc\u011f\u00fcn\u00fc ortaya koymaktad\u0131r. K\u00fc\u00e7\u00fck hatalar bile analiz s\u00fcre\u00e7leri boyunca birikerek etkisini art\u0131r\u0131r. Sonix ile ba\u015flayarak, ki bu hizmet<\/span> <a href=\"https:\/\/sonix.ai\/features\/automated-transcription\"><span style=\"font-weight: 400;\">99%'ye kadar do\u011fruluk<\/span><\/a><span style=\"font-weight: 400;\"> Net ses kayd\u0131, hem GPT-5\u2019e hem de a\u00e7\u0131k kaynakl\u0131 alternatiflere i\u015flenebilecek temiz girdi sa\u011flar. Sonu\u00e7lar yine de kay\u0131t kalitesine ba\u011fl\u0131d\u0131r; bu nedenle, y\u00fcklemeden \u00f6nce g\u00fcr\u00fclt\u00fcy\u00fc giderin ve konu\u015fmac\u0131lar\u0131n\u0131z\u0131 iyi bir \u015fekilde mikrofonla kaydedin.<\/span><\/p>\n<h3><b>Llama 2, belirli transkripsiyon g\u00f6revleri i\u00e7in \u00f6zel olarak geli\u015ftirilmi\u015f modellere k\u0131yasla daha kolay bir \u015fekilde \u00f6zelle\u015ftirilebilir mi?<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Evet. Llama 2\u2019nin ayarlanabilir a\u011f\u0131rl\u0131klar\u0131, belirli verilere y\u00f6nelik ince ayar yap\u0131lmas\u0131na olanak tan\u0131r. T\u0131bbi notlar\u0131, hukuki ifade kay\u0131tlar\u0131n\u0131 veya \u00f6zel terminoloji i\u00e7eren teknik i\u00e7erikleri transkribe ediyorsan\u0131z, Llama 2\u2019yi kelime da\u011farc\u0131\u011f\u0131n\u0131z\u0131 daha iyi anlayabilmesi i\u00e7in ayarlayabilirsiniz. Tescilli modeller genellikle, a\u011f\u0131rl\u0131klara do\u011frudan eri\u015fim yerine, komut sat\u0131r\u0131, veri alma ve sa\u011flay\u0131c\u0131 destekli ayarlama se\u00e7enekleri arac\u0131l\u0131\u011f\u0131yla \u00f6zelle\u015ftirilir.<\/span><\/p>\n<h3><b>Hassas transkripsiyon verileriyle b\u00fcy\u00fck dil modellerinin kullan\u0131lmas\u0131n\u0131n g\u00fcvenlik a\u00e7\u0131s\u0131ndan ne gibi sonu\u00e7lar\u0131 vard\u0131r?<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Tescilli bulut tabanl\u0131 modeller, transkriptlerin harici sunuculara g\u00f6nderilmesini gerektirir; bu durum, certain uyumluluk gereklilikleriyle \u00e7eli\u015febilir. Llama 2 ise tamamen \u015firket i\u00e7inde \u00e7al\u0131\u015ft\u0131r\u0131labilir ve t\u00fcm verileri altyap\u0131n\u0131z i\u00e7inde tutar. Hassas i\u015f y\u00fckleri i\u00e7in, pair Sonix\u2019in<\/span> <a href=\"https:\/\/sonix.ai\/security\"><span style=\"font-weight: 400;\">kurumsal g\u00fcvenlik<\/span><\/a><span style=\"font-weight: 400;\"> SOC 2 Tip II uyumlulu\u011fu, depolama ve aktar\u0131m s\u0131ras\u0131nda \u015fifreleme ile SSO ve SAML deste\u011fi gibi \u00f6zellikler, kendi sunucular\u0131nda bar\u0131nd\u0131rma se\u00e7ene\u011fi ile sunulmaktad\u0131r. HIPAA uyumlu i\u015f ak\u0131\u015flar\u0131, bir BAA anla\u015fmas\u0131 kapsam\u0131nda Medical Sonix arac\u0131l\u0131\u011f\u0131yla kullan\u0131labilir.<\/span><\/p>\n<h3><b>Sonix, Claude, ChatGPT, Cursor veya Codex gibi yapay zeka asistanlar\u0131na ba\u011flanabilir mi?<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Evet. Sonix, \u015fu adreste bir MCP sunucusu sunmaktad\u0131r: <\/span><span style=\"font-weight: 400;\">https:\/\/api.sonix.ai\/mcp<\/span><span style=\"font-weight: 400;\"> Bu \u00f6zellik, uyumlu AI asistanlar\u0131n\u0131n OAuth arac\u0131l\u0131\u011f\u0131yla Sonix medya k\u00fct\u00fcphanenize ve transkriptlerinize g\u00fcvenli bir \u015fekilde eri\u015fmesini sa\u011flar. \u015eu anda MCP eri\u015fimi salt okunurdur; bu sayede asistanlar kay\u0131tlar\u0131 tarayabilir, transkriptleri ba\u011flam i\u00e7ine yerle\u015ftirebilir, d\u0131\u015fa aktar\u0131mlar olu\u015fturabilir ve hesap durumunu kontrol edebilir. MCP, paid planlar\u0131nda kullan\u0131labilir ve yaln\u0131zca hesap sahipleri ile yap\u0131mc\u0131lar ba\u011flant\u0131 yetkisi verebilir. Yeni transkripsiyonlar, \u00e7eviriler, altyaz\u0131lar, \u00f6zetler veya otomatik i\u015f ak\u0131\u015flar\u0131 olu\u015fturmak i\u00e7in bunun yerine Sonix CLI veya REST API'sini kullan\u0131n.<\/span><\/p>","protected":false},"excerpt":{"rendered":"<p>You&#8217;ve invested in a powerful large language model to extract insights from your audio content, but here&#8217;s what most people miss: your LLM is only as smart as your transcript is accurate. Before any advanced language model can summarize your meetings, analyze interviews, or pull key themes from recordings, it needs clean, accurate text to [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-884","post","type-post","status-publish","format-standard","hentry","category-education"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>GPT-5 vs. Llama 2: Which LLM Handles Transcribed Text Best? - Moving AI Forward<\/title>\n<meta name=\"description\" content=\"Compare GPT-5 vs. Llama 2 for transcript analysis. 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