{"id":4643,"date":"2025-06-10T07:47:07","date_gmt":"2025-06-10T07:47:07","guid":{"rendered":"https:\/\/bulutistan.com\/blog\/?p=4643"},"modified":"2025-06-10T07:47:07","modified_gmt":"2025-06-10T07:47:07","slug":"openai-whisper-nedir-diger-ses-tanima-modellerinden-farki-nedir","status":"publish","type":"post","link":"https:\/\/bulutistan.com\/blog\/openai-whisper-nedir-diger-ses-tanima-modellerinden-farki-nedir\/","title":{"rendered":"OpenAI Whisper Nedir? Di\u011fer Ses Tan\u0131ma Modellerinden Fark\u0131 Nedir?"},"content":{"rendered":"

Konu\u015fma tan\u0131ma modelleri ve API’leri, sa\u011fl\u0131k hizmetleri, m\u00fc\u015fteri hizmetleri, \u00e7evrimi\u00e7i toplant\u0131lar ve e\u011flence sekt\u00f6r\u00fc dahil olmak \u00fczere \u00e7e\u015fitli sekt\u00f6rler i\u00e7in uygulamalar olu\u015fturmada \u00e7ok \u00f6nemlidir.<\/p>\n

Bu t\u00fcr uygulamalara g\u00fc\u00e7 sa\u011flamak i\u00e7in g\u00fcn\u00fcm\u00fczde mevcut olan bir\u00e7ok se\u00e7enek aras\u0131nda b\u00fcy\u00fck teknoloji sa\u011flay\u0131c\u0131lar\u0131, a\u00e7\u0131k kaynak modelleri ve \u00f6zel API sa\u011flay\u0131c\u0131lar\u0131 bulunmaktad\u0131r. Bunlar\u0131n her biri, i\u015fletmelerin ve geli\u015ftiricilerin farkl\u0131 ihtiya\u00e7lar\u0131n\u0131 kar\u015f\u0131layan benzersiz \u00f6zellikler ve yetenekler sunmaktad\u0131r.<\/p>\n

Bu a\u015famada devreye giren teknolojilerden biri de OpenAI Whisper\u2019d\u0131r. Peki OpenAI Whisper tam olarak nedir?<\/p>\n

OpenAI Whisper Nedir?\u00a0<\/strong><\/h2>\n

Whisper ASR, OpenAI taraf\u0131ndan piyasaya s\u00fcr\u00fclen bir sinir a\u011f\u0131d\u0131r. 680.000 saatlik \u00e7ok dilli ses \u00fczerinde e\u011fitilen model, do\u011frulu\u011fu ve \u00e7ok dilli yetenekleri nedeniyle a\u00e7\u0131k kaynak topluluklar\u0131 ve i\u015fletmeler aras\u0131nda olduk\u00e7a pop\u00fclerdir.<\/p>\n

Yapay zeka transkripsiyonuna veya konu\u015fmadan metne ek olarak, model 99 dilden \u0130ngilizceye \u00e7eviri yapmaktad\u0131r. Whisper ailesi, 39 milyon ila 1,55 milyar parametre aras\u0131nda de\u011fi\u015fen be\u015f boyutta mevcut olup geli\u015ftiricilerin do\u011fruluk ve i\u015flem s\u00fcresi aras\u0131nda uygun dengeyi kurmas\u0131na olanak tan\u0131r. Whisper’a \u00f6zel kelime da\u011farc\u0131\u011f\u0131 eklenebilir veya ek diller, \u00f6zel jargon ve daha fazlas\u0131 i\u00e7in modele ince ayar yap\u0131labilir.<\/p>\n

Whisper \u015fu anda hem a\u00e7\u0131k kaynakl\u0131 (OSS) bir model hem de bir API olarak mevcuttur.<\/p>\n

OpenAI Whisper’\u0131n Temel \u00d6zellikleri<\/strong><\/h3>\n
    \n
  • \u00c7ok Dilli Destek:\u00a0<\/strong>99’dan fazla dili tan\u0131yabilir ve yaz\u0131ya d\u00f6kebilir.<\/li>\n
  • Y\u00fcksek Do\u011fruluk:\u00a0<\/strong>\u00c7e\u015fitli ses ko\u015fullar\u0131nda son teknoloji performans g\u00f6sterir.<\/li>\n
  • A\u00e7\u0131k Kaynak Eri\u015filebilirli\u011fi:\u00a0<\/strong>Geli\u015ftiriciler ve ara\u015ft\u0131rmac\u0131lar i\u00e7in \u00fccretsiz olarak kullan\u0131labilir.<\/li>\n
  • Varyasyonlara Dayan\u0131kl\u0131:<\/strong>\u00a0Farkl\u0131 ses kaliteleri, arka plan g\u00fcr\u00fclt\u00fcs\u00fc ve konu\u015fmac\u0131 aksanlar\u0131yla ba\u015fa \u00e7\u0131kabilir.<\/li>\n<\/ul>\n

    Whisper’\u0131n sinir a\u011f\u0131 inan\u0131lmaz derecede \u00e7ok y\u00f6nl\u00fc olacak \u015fekilde tasarlanm\u0131\u015ft\u0131r, bu da onu karma\u015f\u0131k konu\u015fma tan\u0131ma zorluklar\u0131 i\u00e7in ba\u015fvurulacak bir \u00e7\u00f6z\u00fcm haline getirir. Transformat\u00f6r tabanl\u0131 mimarisi, \u00e7e\u015fitli dilsel ba\u011flamlarda \u00f6\u011frenmesine ve uyum sa\u011flamas\u0131na olanak tan\u0131yarak konu\u015fmadan metne alan\u0131nda yeni bir standart olu\u015fturur.<\/p>\n

    Bununla birlikte, Whisper etkileyici olsa da, herkese uyan tek bir \u00e7\u00f6z\u00fcm de\u011fildir. Ger\u00e7ek zamanl\u0131 transkripsiyon, kurumsal d\u00fczeyde da\u011f\u0131t\u0131m veya \u00f6zel end\u00fcstri gereksinimleri gibi belirli kullan\u0131m durumlar\u0131na ba\u011fl\u0131 olarak, alternatif \u00e7\u00f6z\u00fcmler daha \u00f6zel avantajlar sunabilir.<\/p>\n

    OpenAI Whisper Nas\u0131l \u00c7al\u0131\u015f\u0131r?<\/strong><\/h2>\n

    OpenAI Whisper, temel olarak yapay zeka sistemlerine bilin\u00e7alt\u0131 \u00f6\u011frenme yetenekleri a\u015f\u0131layarak, \u00e7e\u015fitli veri girdilerinden karma\u015f\u0131k kal\u0131plar\u0131, korelasyonlar\u0131 ve bilgileri ay\u0131rt etmelerine olanak tan\u0131ma yetene\u011fi ile karakterize edilir. Geli\u015fmi\u015f sinir a\u011f\u0131 mimarileri ve bili\u015fsel modeller sayesinde OpenAI Whisper, yapay zeka sistemlerinde otonom bilgi edinimi ve adaptasyonu i\u00e7in bir kataliz\u00f6r g\u00f6revi g\u00f6r\u00fcr.<\/p>\n

    OpenAI Whisper’\u0131n operasyonel \u00e7er\u00e7evesi, \u00e7ok y\u00f6nl\u00fc veri kaynaklar\u0131ndan \u00f6rt\u00fck bilgi ve kal\u0131plar\u0131n \u00f6z\u00fcmsenmesini kolayla\u015ft\u0131ran karma\u015f\u0131k derin \u00f6\u011frenme algoritmalar\u0131n\u0131n ve sinir a\u011f\u0131 mimarilerinin entegrasyonunu i\u00e7erir. Bu uygulama, yapay zeka sistemlerinin bili\u015fsel modellerini \u00f6\u011frenmelerini, uyarlamalar\u0131n\u0131 ve iyile\u015ftirmelerini sa\u011flayarak karar verme ve problem \u00e7\u00f6zme kapasitelerini geli\u015ftirir.<\/p>\n

    Whisper Mimarisi Bile\u015fenleri<\/strong><\/h2>\n

    Whisper modeli \u00f6ncelikle ses par\u00e7alar\u0131n\u0131 i\u015flemek ve bunlar\u0131 metin segmentlerine d\u00f6n\u00fc\u015ft\u00fcrmek i\u00e7in kodlay\u0131c\u0131 ve kod \u00e7\u00f6z\u00fcc\u00fc bloklardan olu\u015fur.<\/p>\n

    A\u015fa\u011f\u0131da bir ses dosyas\u0131 \u00fczerinde ger\u00e7ekle\u015ftirilen ad\u0131m ad\u0131m i\u015fleme ve bunun metinsel bir \u00e7\u0131kt\u0131ya nas\u0131l d\u00f6n\u00fc\u015ft\u00fc\u011f\u00fcn\u00fc inceleyebilirsiniz.<\/p>\n

    Girdi Segmentasyonu<\/strong><\/h3>\n

    Whispers \u00e7ekirdek mimarisi 30 saniyelik ses par\u00e7alar\u0131n\u0131 s\u0131rayla i\u015flemek \u00fczere tasarlanm\u0131\u015ft\u0131r. Bu par\u00e7alar, log-Mel spektrogramlar\u0131na d\u00f6n\u00fc\u015ft\u00fcr\u00fcld\u00fckleri \u00f6n i\u015fleme tabi tutulur. Bu spektrogramlar sesin temel akustik \u00f6zelliklerini yakalayarak konu\u015fma sinyalinin zengin bir temsilini sa\u011flar.<\/p>\n

    Kodlay\u0131c\u0131 Blo\u011fu<\/strong><\/h3>\n

    Daha sonra kodlanm\u0131\u015f log-Mel spektrogramlar\u0131 bir kodlay\u0131c\u0131dan ge\u00e7irilir. Bu kodlay\u0131c\u0131 ses bilgisini i\u015fler ve t\u00fcm zengin ayr\u0131nt\u0131lar\u0131 yakalayan kompakt bir temsil olu\u015fturur.<\/p>\n

    Kod \u00c7\u00f6z\u00fcc\u00fc Blo\u011fu<\/strong><\/h3>\n

    Ard\u0131ndan, kodlanm\u0131\u015f temsil bir \u00e7\u00f6z\u00fcc\u00fcye (decoder) aktar\u0131l\u0131r. \u00c7\u00f6z\u00fcc\u00fcn\u00fcn temel g\u00f6revi, kodlanm\u0131\u015f ses bilgisine dayanarak kar\u015f\u0131l\u0131k gelen metin altyaz\u0131lar\u0131n\u0131 tahmin etmektir. Model, dil tan\u0131ma, ifade d\u00fczeyinde zaman damgalar\u0131, \u00e7ok dilli transkripsiyon ve konu\u015fmadan metne \u00e7eviri gibi ek g\u00f6revleri ger\u00e7ekle\u015ftirmek i\u00e7in \u00f6zel semboller (special tokens) kullan\u0131r.<\/p>\n

    OpenAI Whisper Uygulamalar\u0131<\/strong><\/h2>\n

    OpenAI Whisper, \u00e7e\u015fitli sekt\u00f6rlerde pratik uygulamalara sahiptir ve kullan\u0131c\u0131lar i\u00e7in \u00fcretkenli\u011fi ve eri\u015filebilirli\u011fi \u00f6nemli \u00f6l\u00e7\u00fcde art\u0131r\u0131r.<\/p>\n

    1. Transkripsiyon Hizmetleri<\/strong><\/h3>\n

    Whisper’\u0131n farkl\u0131 aksanlar ve zorlu ses ortamlar\u0131 konusundaki uzmanl\u0131\u011f\u0131, r\u00f6portajlar\u0131, podcast’leri ve dersleri do\u011fru transkriptlere d\u00f6n\u00fc\u015ft\u00fcrme otomasyonunu d\u00f6n\u00fc\u015ft\u00fcrmektedir. \u00c7ok dilli deste\u011fi de farkl\u0131 dillerdeki de\u011ferini art\u0131rmaktad\u0131r.<\/p>\n

    2. Sanal Asistanlar<\/strong><\/h3>\n

    Whisper, modern LLM tabanl\u0131 sanal asistanlarda transkripsiyon g\u00f6revlerine g\u00fc\u00e7 sa\u011flayabilir. Ger\u00e7ek zamanl\u0131 performans\u0131, ses kontroll\u00fc ak\u0131ll\u0131 ev cihazlar\u0131nda veya sohbet robotlar\u0131nda zamanlama ve bilgi alma gibi g\u00f6revleri y\u00fcr\u00fctmek i\u00e7in verimli konu\u015fma i\u015fleme sa\u011flar.<\/p>\n

    3. Engelliler i\u00e7in Eri\u015filebilirlik Uygulamalar\u0131<\/strong><\/h3>\n

    Whisper, eri\u015filebilirlik \u00f6zelliklerini geli\u015ftirmede ve teknolojiyi engelli bireyler i\u00e7in daha kapsay\u0131c\u0131 hale getirmede hayati \u00f6neme sahiptir. Ses kontroll\u00fc aray\u00fczler, altyaz\u0131 ve canl\u0131 etkinlikler i\u00e7in ger\u00e7ek zamanl\u0131 transkripsiyon sa\u011flayarak Whisper, bilgi ve hizmetlere e\u015fit eri\u015fim sa\u011flar.<\/p>\n

    4. M\u00fc\u015fteri Deste\u011fi<\/strong><\/h3>\n

    Whisper, m\u00fc\u015fteri \u00e7a\u011fr\u0131lar\u0131n\u0131 ger\u00e7ek zamanl\u0131 olarak yaz\u0131ya d\u00f6kerek m\u00fc\u015fteri hizmetlerini ve \u00e7a\u011fr\u0131 merkezi operasyonlar\u0131n\u0131 iyile\u015ftirir. Bu, temsilcilerin Whisper transkripsiyonu ger\u00e7ekle\u015ftirirken m\u00fc\u015fteri ihtiya\u00e7lar\u0131n\u0131 kar\u015f\u0131lamaya odaklanmas\u0131na olanak tan\u0131yarak verimlili\u011fi, kalite g\u00fcvencesini ve uyumluluk izlemesini art\u0131r\u0131r.<\/p>\n

    5. Doktor-Hasta Etkile\u015fiminin Yaz\u0131ya D\u00f6k\u00fclmesi<\/strong><\/h3>\n

    Sa\u011fl\u0131k hizmetlerinde, hasta etkile\u015fimlerinin belgelenmesinde, idari y\u00fcklerin azalt\u0131lmas\u0131nda ve do\u011fru t\u0131bbi kay\u0131tlar\u0131n sa\u011flanmas\u0131nda profesyonellere yard\u0131mc\u0131 olur. Hasta notlar\u0131n\u0131n olu\u015fturulmas\u0131n\u0131 otomatikle\u015ftirerek yapay zeka tabanl\u0131 sa\u011fl\u0131k uygulamalar\u0131n\u0131 daha da g\u00fc\u00e7lendirir.<\/p>\n

    6. Otomatik \u0130\u00e7erik Olu\u015fturma<\/strong><\/h3>\n

    Whisper, transkripsiyon yoluyla i\u00e7erik \u00fcretimini h\u0131zland\u0131rarak i\u00e7erik olu\u015fturuculara fayda sa\u011flar. Konu\u015fmay\u0131 yaz\u0131ya d\u00f6kerek ve \u00e7evirerek uluslararas\u0131 ileti\u015fimi kolayla\u015ft\u0131r\u0131r. Ayr\u0131ca, ara\u00e7 kullan\u0131m\u0131 esnas\u0131nda ortamlar\u0131nda Whisper eller serbest kontrol sa\u011flayarak g\u00fcvenli\u011fi art\u0131r\u0131r. Ayr\u0131ca, ses verilerini analiz ederek g\u00fcvenlik ve g\u00f6zetime yard\u0131mc\u0131 olur.<\/p>\n

    OpenAI Whisper\u2019\u0131n Di\u011fer Ses Tan\u0131ma Modellerinden Fark\u0131 Nedir?<\/strong><\/h2>\n

    Ses tan\u0131ma pazar\u0131, OpenAI Whisper ile rekabet eden sa\u011flam bir alternatif ekosistemi sunmaktad\u0131r. Her platform, farkl\u0131 kullan\u0131m durumlar\u0131na ve teknik gereksinimlere hitap eden benzersiz g\u00fc\u00e7l\u00fc y\u00f6nler getirir.<\/p>\n\n\n\n\n\n\n\n\n\n
    Hizmet<\/strong><\/td>\nDil Deste\u011fi<\/strong><\/td>\nDo\u011fruluk Oran\u0131<\/strong><\/td>\nFiyat Modeli<\/strong><\/td>\nEn Uygun Kullan\u0131m\u00a0<\/strong><\/td>\n<\/tr>\n
    OpenAI Whisper<\/strong><\/td>\n99+ dil<\/td>\n%95\u201398<\/td>\n\u00dccretsiz \/ A\u00e7\u0131k kaynak<\/td>\nAra\u015ft\u0131rmalar & Esnek Projeler<\/td>\n<\/tr>\n
    Google Speech-to-Text<\/strong><\/td>\n125+ dil<\/td>\n%90\u201395<\/td>\nDakika ba\u015f\u0131 \u00fccret<\/td>\nKurumsal & B\u00fcy\u00fck \u00d6l\u00e7ekli Uygulamalar<\/td>\n<\/tr>\n
    Amazon Transcribe<\/strong><\/td>\n75+ dil<\/td>\n%85\u201393<\/td>\nKullan\u0131ma dayal\u0131<\/td>\nAWS Ekosistemi Kullananlar<\/td>\n<\/tr>\n
    AssemblyAI<\/strong><\/td>\n50+ dil<\/td>\n%90\u201396<\/td>\nKademeli fiyatland\u0131rma<\/td>\nGeli\u015ftiriciler & Yeni Giri\u015fimler<\/td>\n<\/tr>\n
    Microsoft Azure<\/strong><\/td>\n100+ dil<\/td>\n%85\u201394<\/td>\nAbonelik tabanl\u0131<\/td>\nB\u00fcy\u00fck Kurumsal Kullan\u0131c\u0131lar<\/td>\n<\/tr>\n
    IBM Watson Speech to Text<\/strong><\/td>\nGeni\u015f dil deste\u011fi<\/td>\n%95<\/td>\nAbonelik Tabanl\u0131<\/td>\nEnd\u00fcstriyel ve \u00d6zel Ortamlar<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    1. Google speech-to-text<\/strong><\/h3>\n

    Google Cloud Speech-to-Text, g\u00fcr\u00fclt\u00fcl\u00fc ortamlarda bile do\u011fru transkripsiyonlar sunmak i\u00e7in tasarlanm\u0131\u015ft\u0131r. \u00d6nemli arka plan g\u00fcr\u00fclt\u00fcs\u00fcn\u00fc etkili bir \u015fekilde i\u015flemek i\u00e7in geli\u015fmi\u015f makine \u00f6\u011frenimi kullan\u0131r.<\/p>\n

    Bu hizmet \u015fantiyeler, restoranlar, toplu ta\u015f\u0131ma ara\u00e7lar\u0131, fabrikalar ve d\u0131\u015f ortamlar gibi ortamlar i\u00e7in \u00e7ok uygundur. \u00d6ne \u00e7\u0131kan \u00f6zelliklerden biri, birden fazla hoparl\u00f6r veya d\u00fc\u015f\u00fck ses kalitesi gibi karma\u015f\u0131k ses senaryolar\u0131n\u0131 ele almada \u00fcst\u00fcn olan ”Geli\u015fmi\u015f Konu\u015fma Tan\u0131ma” modudur.<\/p>\n

    Temel \u00f6zellikler aras\u0131nda otomatik noktalama i\u015faretleri, birden fazla dil deste\u011fi, konu\u015fmac\u0131 g\u00fcnl\u00fc\u011f\u00fc olu\u015fturma, ger\u00e7ek zamanl\u0131 ak\u0131\u015f, \u00f6zel kelime se\u00e7enekleri, otomatik dil alg\u0131lama ve g\u00fcr\u00fclt\u00fc azaltma ara\u00e7lar\u0131yla entegrasyon yer al\u0131r.<\/p>\n

    Google, geli\u015ftiriciler i\u00e7in Python, Java ve Node.js gibi yayg\u0131n olarak kullan\u0131lan programlama dilleri i\u00e7in SDK’lar sa\u011flar. Mevcut uygulamalara sorunsuz entegrasyon i\u00e7in bir REST API’si de mevcuttur.<\/p>\n

    Bulut tabanl\u0131 konu\u015fma tan\u0131ma alan\u0131nda bir g\u00fc\u00e7 merkezi olan Google’\u0131n \u00e7\u00f6z\u00fcm\u00fc a\u015fa\u011f\u0131dakileri sunar:<\/p>\n

      \n
    • Geli\u015fmi\u015f makine \u00f6\u011frenimi modelleri<\/li>\n
    • 125’ten fazla dil deste\u011fi<\/li>\n
    • Ger\u00e7ek zamanl\u0131 transkripsiyon yetenekleri<\/li>\n
    • Esnek fiyatland\u0131rma modelleri<\/li>\n<\/ul>\n

      2. Amazon Transcribe<\/strong><\/h3>\n

      Amazon Transcribe, g\u00fcr\u00fclt\u00fcl\u00fc sesleri etkili bir \u015fekilde i\u015flemek i\u00e7in tasarlanm\u0131\u015f bir konu\u015fmadan metne d\u00f6n\u00fc\u015ft\u00fcrme arac\u0131d\u0131r. Zorlu ses ortamlar\u0131nda bile do\u011fru transkripsiyonlar sunmak i\u00e7in geli\u015fmi\u015f g\u00fcr\u00fclt\u00fc azaltma teknikleri ve \u00f6zel akustik modeller kullan\u0131r.<\/p>\n

      Hizmet, ortam seslerini otomatik olarak filtreleyerek arka plan g\u00fcr\u00fclt\u00fcs\u00fcn\u00fc en aza indirir ve daha net sonu\u00e7lar elde edilmesini sa\u011flar. Hem canl\u0131 altyaz\u0131 i\u00e7in ger\u00e7ek zamanl\u0131 ak\u0131\u015f\u0131 hem de \u00f6nceden kaydedilmi\u015f ses i\u00e7in toplu i\u015flemeyi destekler ve \u00e7e\u015fitli ses formatlar\u0131 ile uyumludur.<\/p>\n

      Amazon Web Services’in ses tan\u0131ma hizmeti a\u015fa\u011f\u0131daki \u00f6zellikleriyle \u00f6ne \u00e7\u0131kar:<\/p>\n

        \n
      • AWS ekosistemi ile derin entegrasyon<\/li>\n
      • Otomatik dil tan\u0131mlama<\/li>\n
      • \u00d6zel kelime deste\u011fi<\/li>\n
      • T\u0131bbi ve finansal transkripsiyon uzmanl\u0131klar\u0131<\/li>\n<\/ul>\n

        3. Assemblyai<\/strong><\/h3>\n

        Geli\u015ftirici dostu bir platform olarak bilinen Assemblyai a\u015fa\u011f\u0131daki \u00f6zellikleriyle \u00f6ne \u00e7\u0131kar:<\/p>\n

          \n
        • Y\u00fcksek do\u011fruluklu yapay zeka modelleri<\/li>\n
        • \u00d6zel ses zekas\u0131 \u00f6zellikleri<\/li>\n
        • Kolay API entegrasyonu<\/li>\n
        • \u00d6l\u00e7eklenebilir \u00e7\u00f6z\u00fcmler i\u00e7in rekabet\u00e7i fiyatland\u0131rma<\/li>\n<\/ul>\n

          4. Microsoft Azure Speech Service<\/strong><\/h3>\n

          Microsoft Azure Speech Service, g\u00fcr\u00fclt\u00fcl\u00fc ortamlarda bile iyi performans g\u00f6sterecek \u015fekilde tasarlanm\u0131\u015ft\u0131r. Konu\u015fmay\u0131 net tutarken arka plan seslerini en aza indirmek i\u00e7in geli\u015fmi\u015f g\u00fcr\u00fclt\u00fc azaltma teknikleri kullan\u0131r. Bu da onu end\u00fcstriyel tesisler, d\u0131\u015f mekanlar veya kalabal\u0131k alanlar i\u00e7in g\u00fc\u00e7l\u00fc bir se\u00e7enek haline getirir.<\/p>\n

          Temel \u00f6zellikler aras\u0131nda akustik yank\u0131 giderme, g\u00fcr\u00fclt\u00fc bast\u0131rma ve uzak alan konu\u015fma tan\u0131ma yer al\u0131r. Bu ara\u00e7lar, zorlu ortamlarda bile transkripsiyon do\u011frulu\u011funu art\u0131rmak i\u00e7in birlikte \u00e7al\u0131\u015f\u0131r. Hizmet birden fazla ses format\u0131n\u0131 destekler ve standart API’ler arac\u0131l\u0131\u011f\u0131yla di\u011fer uygulamalara kolayca ba\u011flanarak \u00e7ok \u00e7e\u015fitli uygulamalar i\u00e7in uygun hale gelir.<\/p>\n

          Microsoft’un teklifi a\u015fa\u011f\u0131dakileri sa\u011flar:<\/p>\n

            \n
          • Kapsaml\u0131 konu\u015fma tan\u0131ma yetenekleri<\/li>\n
          • \u00d6zel konu\u015fma modeli e\u011fitimi<\/li>\n
          • Ger\u00e7ek zamanl\u0131 ve toplu transkripsiyon<\/li>\n
          • G\u00fc\u00e7l\u00fc kurumsal g\u00fcvenlik \u00f6zellikleri<\/li>\n<\/ul>\n

            5. IBM Watson Speech to Text<\/strong><\/h3>\n

            IBM Watson Speech to Text, g\u00fcr\u00fclt\u00fcl\u00fc ortamlarda bile iyi performans g\u00f6sterecek \u015fekilde tasarlanm\u0131\u015ft\u0131r. Arka planda parazit olsa bile transkripsiyonu do\u011fru tutmak i\u00e7in geli\u015fmi\u015f g\u00fcr\u00fclt\u00fc d\u00fczeltme ve akustik modelleme kullan\u0131r.<\/p>\n

            \u00d6ne \u00e7\u0131kan bir \u00f6zelli\u011fi de konu\u015fmac\u0131 diyarizasyonudur. Bu, \u00fcst \u00fcste binen seslerin belirlenmesine ve ayr\u0131lmas\u0131na yard\u0131mc\u0131 olarak, g\u00fcr\u00fclt\u00fc seviyelerinin y\u00fcksek olabilece\u011fi toplant\u0131lar\u0131, konferanslar\u0131 veya grup tart\u0131\u015fmalar\u0131n\u0131 yaz\u0131ya d\u00f6kmek i\u00e7in harika bir ara\u00e7 haline getirir.<\/p>\n

            Platform ayr\u0131ca \u00e7a\u011fr\u0131 merkezleri, medya ve end\u00fcstriyel ortamlar gibi \u00f6zel kullan\u0131mlar i\u00e7in \u00f6zel akustik modeller de sunar. Fiyatland\u0131rma esnektir ve daha b\u00fcy\u00fck \u00f6l\u00e7ekli kurumsal ihtiya\u00e7lar i\u00e7in toplu indirimlerle birlikte kulland\u0131k\u00e7a \u00f6de modeli sunar.<\/p>\n

            Temel \u00f6zellikler a\u015fa\u011f\u0131dakileri i\u00e7erir:<\/p>\n

              \n
            • Say\u0131lar, para birimi ve tarihler i\u00e7in ak\u0131ll\u0131 bi\u00e7imlendirme<\/li>\n
            • \u00d6zelle\u015ftirilebilir k\u00fcf\u00fcr filtreleri<\/li>\n
            • Arka plan g\u00fcr\u00fclt\u00fc s\u0131n\u0131fland\u0131rmas\u0131<\/li>\n
            • D\u00fc\u015f\u00fck gecikmeli ger\u00e7ek zamanl\u0131 i\u015fleme<\/li>\n<\/ul>\n

              Geli\u015ftiriciler, Python, Java ve Node.js i\u00e7in mevcut SDK’lar ile REST API’lerini veya WebSocket protokollerini kullanarak Watson’\u0131 entegre edebilirler. WAV, MP3 ve FLAC gibi pop\u00fcler ses formatlar\u0131n\u0131 destekler.<\/p>\n

              Son g\u00fcncellemeler, sistemin tekrarlayan arka plan g\u00fcr\u00fclt\u00fclerine uyum sa\u011flamas\u0131na ve zaman i\u00e7inde do\u011frulu\u011funu art\u0131rmas\u0131na olanak tan\u0131yan s\u00fcrekli \u00f6\u011frenme \u00f6zelli\u011fini getirmi\u015ftir. Bu da onu \u00f6zellikle tutarl\u0131 performans\u0131n \u00e7ok \u00f6nemli oldu\u011fu end\u00fcstriyel ve in\u015faat ortamlar\u0131nda kullan\u0131\u015fl\u0131 k\u0131lar.<\/p>\n

              Bu alternatiflerin her biri benzersiz avantajlar sunar ve se\u00e7imi belirli proje gereksinimlerine, b\u00fct\u00e7e k\u0131s\u0131tlamalar\u0131na ve teknik ekosisteme ba\u011fl\u0131 hale getirir.<\/p>\n

              Sonu\u00e7 olarak OpenAI Whisper, \u00e7ok \u00e7e\u015fitli uygulamalar i\u00e7in \u00f6nemli potansiyele sahip g\u00fc\u00e7l\u00fc bir ASR sistemidir. Yeteneklerini ve s\u0131n\u0131rlamalar\u0131n\u0131 anlayarak, Whisper’\u0131n konu\u015fma tan\u0131ma ihtiya\u00e7lar\u0131n\u0131z i\u00e7in do\u011fru se\u00e7im olup olmad\u0131\u011f\u0131n\u0131 belirleyebilirsiniz.<\/p>\n

              En \u00c7ok sorulan Sorular<\/strong><\/h2>\n

              1. Whisper AI ne i\u00e7in kullan\u0131l\u0131r?<\/strong><\/h3>\n

              Whisper AI, konu\u015fulan kelimeleri yaz\u0131l\u0131 metne d\u00f6n\u00fc\u015ft\u00fcrebilen bir otomatik konu\u015fma tan\u0131ma (ASR) motorudur. Konu\u015fmadan metne transkripsiyon, dil tan\u0131mlama ve \u00e7eviri dahil olmak \u00fczere \u00e7e\u015fitli uygulamalar i\u00e7in kullan\u0131labilir.<\/p>\n

              2. Whisper API nedir?<\/strong><\/h3>\n

              Whisper API, geli\u015ftiricilerin Whisper’\u0131 uygulamalar\u0131na entegre etmelerini sa\u011flayan bir programlama aray\u00fcz\u00fcd\u00fcr. API, konu\u015fmadan metne transkripsiyon, dil tan\u0131mlama ve konu\u015fma \u00e7evirisi dahil olmak \u00fczere Whisper’\u0131n t\u00fcm i\u015flevlerine eri\u015fim sa\u011flar.<\/p>\n

              3. Whisper OpenAI \u00fccretsiz mi?<\/strong><\/h3>\n

              Whisper a\u00e7\u0131k kaynakl\u0131 bir modeldir ve herkesin kullanmas\u0131 ve de\u011fi\u015ftirmesi i\u00e7in \u00fccretsiz olarak kullan\u0131labilir. Ancak, daha h\u0131zl\u0131 i\u015flem i\u00e7in \u00f6zel GPU deste\u011fi gerektirir.<\/p>\n

              4. Whisper’\u0131n di\u011fer yapay zekalardan fark\u0131 nedir?<\/strong><\/h3>\n

              Whisper, \u00e7ok dilli konu\u015fmay\u0131 i\u015fleme yetene\u011fi ve dil tan\u0131mlama \u00f6zelli\u011fi ile benzersizdir. OpenAI’nin GPT-3 dil modelinde kullan\u0131lan Transformer mimarisinin \u00fczerine in\u015fa edilmi\u015ftir. Whisper ayr\u0131ca bir konu\u015fma tan\u0131ma modeli olan Whisper modelini de i\u00e7erir.<\/p>\n

              5. Whisper \u00fcretken yapay zeka olarak kabul edilir mi?<\/strong><\/h3>\n

              Whisper, ba\u011flamdan \u00e7\u0131kar\u0131m yapmak ve transkriptteki eksikleri tahmin etmek i\u00e7in (\u00f6rne\u011fin, t\u00fcm c\u00fcmlelerin ba\u011flam\u0131n\u0131 anlayarak) \u00fcretken yapay zeka y\u00f6ntemlerini kullan\u0131r.<\/p>\n

              6. OpenAI Whisper a\u00e7\u0131k kaynak kodlu mu?<\/strong><\/h3>\n

              Evet, OpenAI Whisper a\u00e7\u0131k kaynak kodludur. Whisper, \u00e7e\u015fitli seslerden olu\u015fan b\u00fcy\u00fck bir veri k\u00fcmesi \u00fczerinde e\u011fitilmi\u015f genel ama\u00e7l\u0131 bir konu\u015fma tan\u0131ma modelidir. \u0130lk olarak Eyl\u00fcl 2022’de a\u00e7\u0131k kaynakl\u0131 yaz\u0131l\u0131m olarak piyasaya s\u00fcr\u00fclm\u00fc\u015ft\u00fcr. Model ve \u00e7\u0131kar\u0131m kodu GitHub’da mevcuttur. Aksanlara, arka plan g\u00fcr\u00fclt\u00fcs\u00fcne ve teknik dile kar\u015f\u0131 dayan\u0131kl\u0131 olacak \u015fekilde tasarlanm\u0131\u015ft\u0131r. Whisper’\u0131n a\u00e7\u0131k kaynak yap\u0131s\u0131, geli\u015ftiricilerin ve ara\u015ft\u0131rmac\u0131lar\u0131n onu kendi \u00f6zel ihtiya\u00e7lar\u0131 i\u00e7in kullanmalar\u0131na ve de\u011fi\u015ftirmelerine olanak tan\u0131yarak konu\u015fma tan\u0131ma teknolojisinin ilerlemesine katk\u0131da bulunur.<\/p>\n","protected":false},"excerpt":{"rendered":"Konu\u015fma tan\u0131ma modelleri ve API’leri, sa\u011fl\u0131k hizmetleri, m\u00fc\u015fteri hizmetleri, \u00e7evrimi\u00e7i toplant\u0131lar ve e\u011flence sekt\u00f6r\u00fc dahil olmak \u00fczere \u00e7e\u015fitli…\n","protected":false},"author":1,"featured_media":4644,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"csco_singular_sidebar":"","csco_page_header_type":"","csco_appearance_grid":"","csco_page_load_nextpost":"","csco_post_video_location":[],"csco_post_video_location_hash":"","csco_post_video_url":"","csco_post_video_bg_start_time":0,"csco_post_video_bg_end_time":0},"categories":[4],"tags":[],"yoast_head":"\nOpenAI Whisper Nedir? 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