在线体验地址：
https://www.sesame.com/research/crossing_the_uncanny_valley_of_voice#demo
看看这个，这是我见过对话最自然的语音大模型，可惜目前只支持英语，这个 demo 实际体验效果在 reddit 上被吹爆了，而官方预告说未来会在 1-2 周内开源，目前 github 上这个还正式放源码的空项目 star 已经超过 3.4k 了
Github 地址：
https://github.com/SesameAILabs/csm
模型部分描述：
Dataset: We use a large dataset of publicly available audio, which we transcribe, diarize, and segment. After filtering, the dataset consists of approximately one million hours of predominantly English audio.
Model Sizes: We trained three model sizes, delineated by the backbone and decoder sizes:
Tiny: 1B backbone, 100M decoder
Small: 3B backbone, 250M decoder
Medium: 8B backbone, 300M decoder
Each model was trained with a 2048 sequence length (~2 minutes of audio) over five epochs.
https://www.sesame.com/research/crossing_the_uncanny_valley_of_voice#demo
看看这个，这是我见过对话最自然的语音大模型，可惜目前只支持英语，这个 demo 实际体验效果在 reddit 上被吹爆了，而官方预告说未来会在 1-2 周内开源，目前 github 上这个还正式放源码的空项目 star 已经超过 3.4k 了
Github 地址：
https://github.com/SesameAILabs/csm
模型部分描述：
Dataset: We use a large dataset of publicly available audio, which we transcribe, diarize, and segment. After filtering, the dataset consists of approximately one million hours of predominantly English audio.
Model Sizes: We trained three model sizes, delineated by the backbone and decoder sizes:
Tiny: 1B backbone, 100M decoder
Small: 3B backbone, 250M decoder
Medium: 8B backbone, 300M decoder
Each model was trained with a 2048 sequence length (~2 minutes of audio) over five epochs.
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