用简单模型捕捉与自闭症和语言障碍诊断相关的语用特征。
Towards Precision Characterization of Communication Disorders using Models of Perceived Pragmatic Similarity
- 基于感知语用相似性构建通用模型，捕捉话语深层含义
- 模型在自闭症和特定语言障碍诊断中有效识别关键语用特征
- 适合临床医生和患者用于辅助评估，尤其数据稀缺场景
通信障碍的诊断与治疗为语音技术应用提供了诸多机会，但现有研究尚未充分关注：病情多样性、语用缺陷的作用以及数据有限的挑战。本文探讨了通用感知语用相似性模型如何克服这些局限。该模型可支持多种临床与用户使用场景，并提供证据表明，一个简单模型即可产生价值，尤其能捕捉与自闭症及特定语言障碍诊断相关的话语特征。
原文摘要 · Abstract (English)
The diagnosis and treatment of individuals with communication disorders offers many opportunities for the application of speech technology, but research so far has not adequately considered: the diversity of conditions, the role of pragmatic deficits, and the challenges of limited data. This paper explores how a general-purpose model of perceived pragmatic similarity may overcome these limitations. It explains how it might support several use cases for clinicians and clients, and presents evidence that a simple model can provide value, and in particular can capture utterance aspects that are relevant to diagnoses of autism and specific language impairment.
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