用AI自动筛查儿童语言障碍，提升评估效率与可及性
Automatic Screening for Children with Speech Disorder using Automatic Speech Recognition: Opportunities and Challenges
- 基于语音识别技术构建儿童语言障碍自动化筛查流程
- 现有方法已验证在真实场景中实现高效评估的可行性
- 适合教育机构与医疗团队快速部署使用
语言是人类生活的基本方面，对沟通、认知、社交和学业发展至关重要。患有语言障碍（SD）的儿童若未及时干预，可能面临长期负面影响。传统语言评估依赖专业言语治疗师（SLPs），但存在资源不足问题。本文综述了可用于自动化语言评估（SLA）流程的技术，重点探讨将自动语音识别（ASR）模型适配于儿童语音的可行性，对比分析现有传统评估与自动化方法，展示人工智能增强型评估系统的应用前景，并讨论实际部署中的可及性与隐私保护等关键挑战。
原文摘要 · Abstract (English)
Speech is a fundamental aspect of human life, crucial not only for communication but also for cognitive, social, and academic development. Children with speech disorders (SD) face significant challenges that, if unaddressed, can result in lasting negative impacts. Traditionally, speech and language assessments (SLA) have been conducted by skilled speech-language pathologists (SLPs), but there is a growing need for efficient and scalable SLA methods powered by artificial intelligence. This position paper presents a survey of existing techniques suitable for automating SLA pipelines, with an emphasis on adapting automatic speech recognition (ASR) models for children's speech, an overview of current SLAs and their automated counterparts to demonstrate the feasibility of AI-enhanced SLA pipelines, and a discussion of practical considerations, including accessibility and privacy concerns, associated with the deployment of AI-powered SLAs.
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