E mōhio ana ngā tohu ki te tauira i kōwhiria - ka kōwhiria kia whakawātea tētahi ki roto i tōna kupu i reira ka puta ai:
Ka pānui tēnei tauira i te kupu noa, nā reira ka whakakāhoretia ngā tohu ā-waitara. Mō te āhua o te tohu-taihi, ka huri ki tētahi tauira whakamārama pēnei i a Orpheus, Bark rānei.
Ko ngā tohu whakawhiwhinga reo māori. I whakawhiwhia e Qwen3-TTS i tēnei rā; Ka tae mai ētahi atu tauira whakamāramatanga.
Kāore tēnei tauira i te tautoko i ngā tohutohu kāhua — ka huri ki tētahi tauira e mahi ana (hei tauira, Qwen3-TTS).
Ka tautuhia ngā tohutohu ā-ringa (wāhi = tohutohu):
-12
+12
Ka whakahaeretia te whakahuahua (0 = pūmau, 1 = tino whakahuahua)
Te taumahatanga tohu whakawātea-whakahaere (nui ake = nui ake te whakahau-whakahaere)
E whakaahua ana i te kāhua reo i roto i te reo māori (ka whakamahia e te Pāpāho tēnei i te wāhi o ngā reo i whakaritea i mua)
He pūāhua taupānga te taupānga taupānga: Ka whakamahia ngā tohu [S1] me [S2] hei tohu i ngā kaikōrero rerekē. Hei tauira: [S1] Hei hei! [S2] Hei, he pēhea koe?
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.
Pai mo: AI assistants, chatbots, conversational AI applications
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.
E tāuru ana i tōna mairā hei haere tonu i te whakaputa kōrero mō te wāteatanga, hei whakaingoatanga rānei mō ngā pūāhua tāpiri 15,000.
Kāore he kupu whakarongo e hiahiatia ana — ka tukuna mai e tātau he pātahitanga ki te tautuhi i tētahi i muri ake nei.
Kua tae te tepe taumata wātea
Kua whakamahia e koe ōna pūāhua wātea 5,000 i ia rā. Whakatū i tētahi kāwanatanga wātea kia whiwhi ai ki ngā pūāhua tāpiri 15,000 tae atu ki ngā pūāhua wātea 10,000 i ia marama.
