Sesame CSM

Sesame CSM TTS

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

Langganan for 5,000 characters limit

Ngresiki teks ing tag SSML kanggo kontrol presisi:

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

Tag kang dipahami model kang dipilih - klik kanggo ngethok siji ing teks sampeyan ing ngendi iku kedadeyan:

Model iki maca teks biasa, mula tag ing baris diabaikan. Kanggo emosi berbasis tag, ganti menyang model ekspresif kaya Orpheus utawa Bark.

Nyathet tembung-tembung standar (kata = tembung):

-12 +12
0.5x 2.0x
Bebas karo Piper, VITS, MeloTTS
Audio sing digawé bakal katon ing kene. Pilih modél, ketik teks, lan pencet Ngembangaké.
Audio Digawé kanthi Sukses
0:00
Unduh Audio Download.srt Link expires in 24h
Ing basa Indonésia, iku tegesé: pribadi. Lisénsi komersial saka $5/mo
TTS.ai? Nyathet kanca-kancamu!

Ngendi 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.

Paling apik kanggo: AI assistants, chatbots, conversational AI applications

Jajal kabeh Sesame CSM swara

Ing cetha

Pangembang
Sesame
Lisénsi
Apache 2.0
Tanggal
premium
Kecepatan
slow
Kloning swara
Ora
Basa
English
Aksara paling akèh
500

Sesame CSM swara

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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