多模态预测自闭症与非自闭症双人对话的感知成功度
原标题：Multi modal perceived conversation success prediction for spontaneous autistic and non-autistic dyadic interactions
AI 摘要
马里兰大学和德克萨斯大学达拉斯分校的研究者提出一种多模态方法，利用发音协调、面部动作单元、音高、强度和轮流发言等特征，在三个包含自闭症与非自闭症参与者的自发双人对话数据集上预测参与者主观感知的对话成功度。研究发现对话成功本质上是多维的，需要多层面分析框架，融合互补模态有望提升预测效果。
正文节选
Multi modal perceived conversation success prediction for spontaneous autistic and non-autistic dyadic interactions Abstract Conversation success is important for communication, social bonds, and well-being and is often reduced in autistic-neurotypical conversations. Previous studies have predicted perceived conversation success using acoustic and lexical features in pediatric autism-enriched samples, or using nonverbal behavior in non-autistic group interactions. Other work has characterized pr