Sesame CSM

Sesame CSM TTS

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

Tia sahihi kwa kiwango cha tabia 5,000

Pakua maandishi yako katika tovuti ya SSML kwa ajili ya udhibiti sahihi:

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

Tag anaelewa mfano unaochaguliwa na unajibu ujumbe huu:

Mfano huu unasomeka maandishi rahisi, kwa hiyo alama za vidole hupuuzwa. Kwa hisia za ndani za watu, geukia kigezo kinachoonesha hisia kama Orfeus au Bark.

Matamshi ya desturi (neno = matamshi):

-12 +12
0.5x 2.0x
Nikiwa huru na Piper, VITS, MelloTTTS
Unaweza kuchagua mfano, maandishi, na kidofo kinachoitwa Genete.
Edio Iliyorekebishwa kwa Mafanikio
0:00
Paketi ya Audio Paketisha.srt Kiungo kinakufa mnamo 24
Safu huru: matumizi ya kibinafsi. Hati ya biashara kutoka dola 5/mo
Fanya hii sauti yako mwenyewe Chokoa sauti kwa sekunde 30
Waeleze rafiki zako kuhusu mapenzi ya TTS.ai?

Habari 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.

Bora kwa: AI assistants, chatbots, conversational AI applications

Ng'ombe wote Sesame CSM sauti

Kutupia jicho

Mbuni
Sesame
Lenzi
Apache 2.0
Tier
premium
Mwendo
slow
Kufanyizwa kwa Sauti
Hapana
Lugha
English
Wahusika wa Max
500

Sesame CSM sauti

Speaker 0

English
Premi Neutral

Speaker 1

English
Premi Neutral

Sesame CSM TTS ngumuSTEGAQ

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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