Sesame CSM

Sesame CSM TTS

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

Ndaftar for 5,000 characters limit

Nglapisi teks ing tag SSML kanggo kontrol sing tepat:

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

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

Model ieu maca teks biasa, jadi tag inline diabaikan. Pikeun emosi dumasar tag, ganti ka model ekspresif kayaning Orpheus atawa Bark.

Nyathet pangucapan standar (kata = pangucapan):

-12 +12
0.5x 2.0x
Bebas karo Piper, VITS, MeloTTS
Audio anu dihasilkeun bakal muncul di dieu. Pilih model, ketok teks, sarta ketok Janji.
Audio berhasil diciptakan
0:00
Muat turun audio Muat turun.srt Link expires in 24h
Kacamatan iki kalebu: Kacamatan Semarang. Lisénsi komersial saka $ 5 / mo
Love TTS.ai? Nyathet kanca-kancamu!

About 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

Nglayar kabeh Sesame CSM suara

Ing cetha

Pangembang
Sesame
Lisensi
Apache 2.0
Tingkat
premium
Kecepatan
slow
Kloning suara
Ora
Basa
English
Karakter paling akeh
500

Sesame CSM suara

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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