温柔白月光 2.0
"温柔白月光 2.0" is an official ListenHub Mandarin Chinese female voice, suited to general audio creation, with a natural and neutral delivery.
ListenHub · Ses kütüphanesi · 12 dil
ListenHub 12 dilde 910 resmî sesle konuşuyor ve hepsi tam burada çalıyor. Sana uyanı bul, sonra doğrudan Metin Seslendirme'ye taşı.
492 sesten 205 tanesi
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12 dilin her birinin kendi sesleri var: Türkçe set, İngilizce setin çevirisi değil, tamamen farklı sesler. Önce yayımlayacağın dili seç.
Kullanım etiketleri bir sesin ne için olduğunu söyler: podcast, sesli kitap, belgesel, çocuk. Stil etiketleri nasıl konuştuğunu söyler. İkisini üst üste koy, birkaç yüz ses bir avuca iner.
Her kart aynı demo cümlesini çalar; böylece karşılaştırdığın şey okuduğu metin değil, sesin kendisi olur.
“Metni seslendir” düğmesi, o ses seçili hâlde Metin Seslendirme'yi açar. Mevcut üç dilin sesleri AI Podcast ve AI Ses kısayollarını da koruyor.
Buradaki her sesin bir speaker ID'si var; ListenHub Skills, MCP sunucusu, CLI ve API ses seçerken hep bu ID'yi kullanır. Bir karttan kopyala, asistanına yapıştır; ürettiği ses o sesle geri gelir.
Projenin içinde tek komut. Claude Code, Cursor, Windsurf ve OpenCode, Agent Skills'i okur.
npx skills add marswaveai/skillslh_sk_ ile başlayan bir anahtar oluştur. Asistanın ilk ihtiyaç duyduğunda sorar, sonrasında saklar.
API anahtarı oluşturYukarıdaki herhangi bir kartta “Agent komutunu kopyala”ya bas. Cümle, ses adı ve speaker ID hazır hâlde gelir — okutmak istediğini ekle ve gönder.
ListenHub'ın "温柔白月光 2.0" sesini (speakerId: doubao-official-ICL_uranus_zh_female_wenroubaiyueguang_tob) kullanarak aşağıdakini sese dönüştür:Hangi kartı seçersen seç, aynı cümle kendi sesiyle gelir.
İkili bölümler, aynı kişinin iki kez konuşması gibi değil, farklı iki insan gibi duyulan iki ses ister. Çifti belirlemeden önce ikisini yan yana dinle.
Sesli kitap ya da uzun bir metin, kırkıncı dakikada sesin hâlâ rahat dinlenip dinlenmediğiyle ayakta kalır. Burada istikrar, çarpıcılıktan önce gelir.
Eğitim içeriği karakterden çok netlik ister — o sesler belgesel ve eğitim etiketlerinin altında toplanır.
Video dublajı ve karakter işleri nötrlük değil, geniş bir yelpaze ister. Karakter ve çok duygulu stillerine göre filtrele; rol yapabilen sesler orada.
Hayır. Bu sayfadaki tüm demolar giriş yapmadan çalar. Hesap ancak kendi sesini üretmek istediğinde devreye girer.
Bugün 12 dilde 910 ses var; her dilin kendi kataloğu bulunuyor. Sayfa, bayat bir sabit sayı yerine gerçekten yayımlanmış olanı sayar.
Dinlemek ücretsiz. Ses üretmek planındaki kredileri harcar; ne kadar harcayacağı formata ve uzunluğa bağlı. Birkaç ses Abonelik işaretli: burada dinleyebilirsin ama onlarla üretmek için plan gerekir.
Kullanım, sesin ne için olduğunu söyler — podcast, sesli kitap, haber sunumu, meditasyon. Stil, nasıl konuştuğunu söyler — nötr, sohbet havasında, karakter, çok duygulu. Uygulamadaki ses seçicinin kullandığı sözlükle aynıdır; burada beğendiğin ses, editörde de beklediğin gibi davranır.
Evet. İkili podcast zaten iki sunucu için yazılır ve ikisini de sen seçersin — önce yan yana dinlemenin işe yaraması tam da bu yüzden.
Evet, ses klonlamayla — 25-35 saniyelik temiz bir kayıt yeter, sesin kendi ses listene eklenir. Klonlama, Metin Seslendirme ile aynı 12 dili destekler. Klonlanan sesler hesabına özel kalır ve bu herkese açık kütüphanede asla görünmez.
Yayımlanan her profilde kullanım ya da stil etiketleri ve yazılı bir açıklama var. Etiketlerle listeyi daralt, niyeti anlamak için açıklamayı oku, sonra sesi kendin değerlendirmek için çal.
Konuyu tek bir sesin baştan sona okuması yerine iki sunucunun konuşarak anlatmasını istediğinde.
Metin zaten hazırsa ve tek eksik onu seslendirmekse.
Söyleyiş önemliyse: tek seferde birden çok ses ya da gerçek bir duyguyla söylenmesi gereken bir cümle.
Konuşan ses kütüphaneden biri olmasın istiyorsan: 30 saniye kaydet, kendi sesini kullan.
listenhub tts create --speaker-id <id>Podcast, anlatım videosu ve slaytlar da aynı bayrağı kullanır.
Tüm sesler, id'ler ve etiketler tek bir düz metin isteğinde, sayfa sayfa gezmeden.
https://listenhub.ai/voices.txt