Sesame CSM

Sesame CSM TTS

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

Upišite se za 5000 ograničenja znakova

Umotaj svoj tekst u SSML oznake za preciznu kontrolu:

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

Oznake odabrani model razumije — kliknite da bacite jedan u vaš tekst gdje se to događa:

Ovaj model čita običan tekst, tako da inline oznake se zanemaruju. Za tag-based emocije, prebaci na ekspresivni model kao što su Orfeus ili Bark.

Definiši vlastite izgovore (riječ = izgovor):

-12 +12
0.5x 2.0x
Besplatno s Piper, VITS, Melotts
Ovdje će se pojaviti vaš generirani zvuk. Odaberite model, unesite tekst i kliknite Generirati.
Zvučni generisan uspješno
0:00
Preuzmi zvuk Preuzmite.rt Veza isteče za 24 sata
Besplatna uporaba: osobna upotreba. Komercijalna licenca od $5/mo
Reci svojim prijateljima!

O 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.

Najbolje za: AI assistants, chatbots, conversational AI applications

Pregledaj sve Sesame CSM glasovi

Na jedan pogled

Programer
Sesame
Dozvola
Apache 2.0
Nivo
premium
Brzina
slow
Kloniranje glasa
Ne.
Jezici
English
Maks. znakova
500

Sesame CSM glasovi

Speaker 0

English
Premium Neutral

Speaker 1

English
Premium Neutral

Sesame CSM TTS – FAQ

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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