Sesame CSM

Sesame CSM TTS

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

Daftar masuk had 5,000 aksara

Lilitkan teks anda dalam tag SSML untuk kawalan tepat:

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

Tag model dipilih memahami - klik untuk jatuhkan satu ke dalam teks anda di mana ia berlaku:

Model ini membaca teks biasa, jadi tag dalam baris diabaikan. Untuk emosi berdasar tag, beralih ke model ekspresif seperti Orpheus atau Bark.

Tetapkan sebutan tersendiri (perkataan = sebutan):

-12 +12
0.5x 2.0x
Bebas dengan Piper, VITS, MeloTTS
Audio yang dijana akan muncul di sini. Pilih model, masukkan teks, dan klik Janakan.
Audio Dijana Dengan Berjaya
0:00
Muat turun Audio Muat turun.srt Pautan luput dalam 24 jam
Tahap percuma: penggunaan peribadi. Lesen Komersial dari $5/mo
Cinta TTS.ai? Beritahu kawan-kawan anda!

Tentang 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.

Terbaik untuk: AI assistants, chatbots, conversational AI applications

Layari semua Sesame CSM suara

Dengan sekejap mata

Pemaju
Sesame
Lesen
Apache 2.0
Tajuk
premium
Kelajuan
slow
Klon suara
Tidak
Bahasa
English
Aksara maksimum
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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