arXiv cs.AI· Al Varrel Putra Kusuma, Fernando Bello, Joshua Brown·· 3 天前AI 评分23
AphaVoice：面向失语症患者模拟的文本转语音模型
AphaVoice: Text-to-Speech Model for Aphasia Patient Simulation
AI 导读
研究提出 AphaVoice，一个专门合成高度逼真失语症语音的 TTS 框架，用于缓解语言治疗临床资源不足下的医护人员培训难题。与当前最先进 TTS 系统相比，AphaVoice 在时间指标上更能捕捉失语症的不流畅临床特征，并持续保持说话人身份一致。该模型借助潜空间偏移（latent space shifting）支持多说话人生成而不牺牲语音真实感，论文已被 IEEE SLT 2026 接收。
正文 · 原文
Abstract:While language therapy is the primary treatment for post-stroke aphasia, limited clinical resources often restrict patient access to proper care. Addressing this gap requires reliable training simulations for medical professionals. However, current AI efforts focus almost exclusively on speech processing, leaving speech generation largely unexplored. This study introduces AphaVoice, a novel text-to-speech (TTS) framework explicitly engineered to synthesize highly realistic aphasic speech. Evaluated against state-of-the-art TTS systems, AphaVoice demonstrates a superior ability to capture the clinical feature of dysfluency, outperforming existing models in temporal metrics while consistently maintaining speaker identity. By leveraging latent space shifting, the model also supports multi-speaker generation without sacrificing phonetic realism. Ultimately, AphaVoice provides a scalable, high-fidelity tool for medical training and clinical simulation related to aphasia.
| Comments: | Accepted at IEEE Spoken Language Technology (SLT) 2026 |
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.14479 [cs.CL] |
| (or arXiv:2610.14479v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.14479 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Al Varrel Putra Kusuma [view email]
[v1]
Sat, 10 Oct 2026 02:22:51 UTC (765 KB)
来源：arXiv cs.AI · arxiv.org