Step-Audio-EditX Technical Report
We present Step-Audio-EditX, the first open-source LLM-based audio model
excelling at expressive and iterative audio editing encompassing emotion,
speaking style, and paralinguistics alongside robust zero-shot text-to-speech
(TTS) capabilities.Our core innovation lies in leveraging only large-margin
synthetic data, which circumvents the need for embedding-based priors or
auxiliary modules. This large-margin learning approach enables both iterative
control and high expressivity across voices, and represents a fundamental pivot
from the conventional focus on representation-level disentanglement. Evaluation
results demonstrate that Step-Audio-EditX surpasses both MiniMax-2.6-hd and
Doubao-Seed-TTS-2.0 in emotion editing and other fine-grained control tasks.
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Chao Yan
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Boyong Wu
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2025-11-21T09:02:35.705Z
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Boyong Wu
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BoyongWu
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Peng Yang
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Pengfei Tan
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Guoqiang Hu
claimed_verified
2025-11-06T11:48:09.485Z
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Guoqiang Hu
airguoqiang
user
airguoqiang
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Yuxin Zhang
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Xiangyu
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Zhang
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Fei Tian
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Xuerui Yang
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2025-11-06T11:48:11.697Z
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Yang
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Xiangyu Zhang
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2025-11-21T09:02:33.907Z
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Xiangyu
Tonyyouyou1
user
Tonyyouyou1
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Daxin Jiang
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Gang Yu
Step-Audio-EditX Technical Report
We present Step-Audio-EditX, the first open-source LLM-based audio model
excelling at expressive and iterative audio editing encompassing emotion,
speaking style, and paralinguistics alongside robust zero-shot text-to-speech
(TTS) capabilities.Our core innovation lies in leveraging only large-margin
synthetic data, which circumvents the need for embedding-based priors or
auxiliary modules. This large-margin learning approach enables both iterative
control and high expressivity across voices, and represents a fundamental pivot
from the conventional focus on representation-level disentanglement. Evaluation
results demonstrate that Step-Audio-EditX surpasses both MiniMax-2.6-hd and
Doubao-Seed-TTS-2.0 in emotion editing and other fine-grained control tasks.
Step-Audio-EditX, an open-source LLM-based audio model, excels in expressive and iterative audio editing and zero-shot TTS using large-margin synthetic data.
LLM-based audio model expressive audio editing iterative audio editing emotion editing speaking style paralinguistics zero-shot text-to-speech large-margin synthetic data large-margin learning representation-level disentanglement