Sesame CSM

Sesame CSM TTS

A 1B conversational speech model that captures natural dialogue timing, turn-taking, and backchannel responses.

_Gün tertibi 5000 karakter çäk

Metini SSML taglarda dolap dogry kontrol üçin:

<speak><prosody rate="slow">Slow speech</prosody></speak>

Saýlanan model aňlaýan taglar — birini metinde goýmak üçin basyň:

Bu model ýönekeý metin okaýar, şonuň üçin hatda taglar gözden düşürilýär. Tag-based emotions for, switch to an expression model like Orpheus or Bark.

Öz sözleriň terjimesini belli et (söz = terjime):

-12 +12
0.5x 2.0x
Piper, VITS, MeloTTS bilen azat
Siziň döreden audioňyz şu ýerde görüner. Bir model saýlaň, metin girin we döred
Ses mübärek bejerildi
0:00
Ses ýükle .srt ýükle Baglanyşyk 24 sagadyň içinde gutarýar
TTS.ai-ni söýýäňmi? Dostlaryňa aýt!

Habar Sesame CSM

Sesame CSM (Conversational Speech Model) is a 1-billion-parameter model from Sesame designed specifically for the rhythms of human conversation. Built on a Llama backbone paired with an audio codec, it models turn-taking timing, backchannel responses (the small acknowledgements people make while listening), emotional reactions, and overall conversational flow. The result reads less like read-aloud text and more like a real spoken exchange. It is a natural fit for AI assistants, chatbots, and conversational interfaces where the goal is speech that feels responsive and human. CSM is released under Apache 2.0, and access on TTS.ai requires a Hugging Face token at the model level.

Muňa iň gowy: AI assistants, chatbots, conversational AI applications

Ehlini _Gözle Sesame CSM sesler

Bir seretseň

Developer
Sesame
Lisenziýa
Apache 2.0
_Göçür
premium
Tizlik
slow
Ses klonlamak
_Ýok
Diller
English
Maks. karakterler
500

Sesame CSM sesler

Speaker 0

English
Premium Neutral

Speaker 1

English
Premium Neutral

Sesame CSM TTS - Gynançly Soraglar

Conversational speech. It models the natural patterns of dialogue — turn-taking timing, backchannel responses, and emotional reactions — so generated audio sounds like a real conversation rather than synthetic narration.

It is a 1-billion-parameter model built on a Llama backbone with an audio codec for waveform generation.

AI assistants, chatbots, and other conversational applications where responsive, human-sounding speech matters more than long-form narration.
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