Sesame CSM

Sesame CSM TTS

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

Prijavite se za ograničenje od 5.000 znakova

Omotajte tekst u SSML oznake za preciznu kontrolu:

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

Oznake koje odabrani model razumije — kliknite da biste ih ubacili u tekst gdje se pojavljuju:

Ovaj model čita običan tekst, tako da se inline oznake ignoriraju. Za emocije zasnovane na oznakama, prebacite se na ekspresivni model poput Orpheusa ili Bark-a.

Definirajte vlastite izgovore (riječ = izgovor):

-12 +12
0.5x 2.0x
Besplatno sa Piper, VITS, MeloTTS
Ovdje će se pojaviti vaš generirani audio. Izaberite model, unesite tekst i kliknite na Generiraj.
Audio uspješno generisan
0:00
Preuzmi audio Preuzmi.srt Link istječe za 24h
Free tier: personal use. Komercijalna licenca od $5/mjesečno
Volite TTS.ai?

O meni 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 prvi pogled

Programer
Sesame
Licenca
Apache 2.0
Životinje
premium
Brzina
slow
Kloniranje glasa
Ne, ne, ne.
Jezici
English
Maksimalan broj znakova
500

Sesame CSM glasovi

Speaker 0

English
Premium Neutral

Speaker 1

English
Premium Neutral

Sesame CSM 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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