Sesame CSM

Sesame CSM TTS

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

Anmelden Limit fir 5. 000 Zeichen

Wrap your text in SSML tags for precise control:

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

Tags déi d'gewielt Modell verstinn - klickt fir eng an Ärem Text ze setzen wou se geschitt:

Dëse Modell liest einfache Text, sou datt Inline-Tags ignoréiert ginn. Fir Tag-baséiert Emotiounen, wielt e expressiven Modell wéi Orpheus oder Bark.

Eegen Aussproochen definéieren (Wuert = Aussprooch):

-12 +12
0.5x 2.0x
Free mat Piper, VITS, MeloTTS
Äert generéiert Audio wäert hei erscheinen. Wielt e Modell, gitt Text an a klickt op Generéieren.
Audio gouf erfollegräich generéiert
0:00
Audio erofgelueden Lëscht vu lëtzebuergesche Schrëftsteller Link expires in 24h
Den Haaptuert ass Personnes. Kommerziell Lizenz vun $5/mo
Maacht dat Är eege Stëmm Klonen eng Stëmm an 30 Sekonnen
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Iwwer 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.

Bescht fir: AI assistants, chatbots, conversational AI applications

All sichen Sesame CSM Stimmen

Op ee Bléck

Entwéckler
Sesame
Lizenz
Apache 2.0
Tier
premium
Geschwindegkeet
slow
Sprooche-Klonen
Nee
Sproochen
English
Maximal Zeichen
500

Sesame CSM Stimmen

Speaker 0

English
Premium Neutral

Speaker 1

English
Premium Neutral

Sesame CSM Lëscht vun de 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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