Sesame CSM

Sesame CSM TTS

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

Enskri Limit pou 5,000 karaktè

Wrap ou tèks nan SSML tags pou presizyon kontwòl:

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

Tags ke modèl la chwazi konprann — klike pou mete yon nan tèks ou kote li rive:

Modèl sa a li tèks senp, se poutèt sa atik ki nan liy yo pa pran an kont. Pou efè ki baze sou atik, chanje pou yon modèl ekspresyon tankou Orpheus oswa Bark.

Define prononciations Custom (mot = prononciation):

-12 +12
0.5x 2.0x
Gratis ak Piper, VITS, MeloTTS
Son ou kreye a ap parèt isit la. Chwazi yon modèl, antre tèks la, epi klike Kreye.
Audio Generated Successfully
0:00
Telechaje son Telechaje.srt Link expires in 24h
Free tier: itilize pèsonèl. Lisans Komèsyal soti nan $5/mo
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Atik 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.

Pi bon pou: AI assistants, chatbots, conversational AI applications

Navigue tout Sesame CSM Voy

Yon ti gade

Pwogramè
Sesame
Lisans
Apache 2.0
Nivo
premium
Vitès
slow
Klonaj vwa
Non
Lang
English
Karakteris maksimòm
500

Sesame CSM Voy

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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