COLLABORATIVE RESEARCH: Social-Emotional Analysis of the Language Environment (SEAL): Key Word & Phrase Spotting in Early Childhood Care Settings

O 该项目由发展科学计划和刺激竞争研究的既定计划（EPSCoR）共同资助，儿童在学校和生活中的成功取决于他们是否在早年学习了某些社交和情感技能。为了建立教师促进社会情感学习的能力，需要有一种工具，为教师提供基于数据的反馈，重点是社会情感学习的谈话。这个项目创造了这样一个工具，语言环境的社会情感分析（SEAL）。SEAL使用先进的语音处理算法来自动捕捉幼儿教育课堂中教师实践的一个关键要素，以支持社会情感学习：他们在日常互动中使用语言，特别是单词和短语，这些都可以利用社会情感学习。这种从幼儿教室的录音中自动测量教师的社会情感谈话的方法可以代表一种变革性的方法，以帮助教师更好地支持儿童的社会情感发展（例如，理解、管理和表达情绪）。反过来，这样的工具可以更好地确保幼儿获得确保他们为学校，关系和生活做好准备的技能。为证明SEAL的概念而开展的项目活动包括：（1）根据一项全国性调查和一个有幼儿专业人员参加的焦点小组以及一个专家咨询小组的意见，开发一个社会和情感词汇和短语库;（2）探索教师音频数据，以改进现有的语音处理算法，检测课堂上的成人社会情感关键词汇和短语;以及（3）通过将人类转录与自动检测到的语音数据的基线算法进行比较来检查单词和短语库的初始有效性。这项探索研究旨在提供证据，证明未来完全制定的SEAL解决方案可以产生易于访问和解释的数据，并可供个别教师，教练和幼儿计划使用，以改善旨在促进儿童社会情感结果的实践。最终，就像一个自动化的监视器计数步数，我们设想SEAL可以被教师自己用来监控课堂上的社会情感谈话，并建立能力，以提高幼儿的社会情感能力。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

o This project is jointly funded by the Developmental Science Program and the Established Program to Stimulate Competitive Research (EPSCoR).Children’s success in school and in life depends on whether they have learned certain social and emotional skills in their early years. To build teachers’ capacity to promote social emotional learning, there is a need for tools that provide data-based feedback to teachers on talk that focuses on social-emotional learning. This project creates such a tool, the Social Emotional Analysis of the Language Environment (SEAL). SEAL uses advanced speech processing algorithms to automatically capture a key element of teacher practice in early childhood education classrooms known to support social emotional learning: their use of language, and specifically, words and phrases within everyday interactions that tap into social emotional learning. This automatic measurement of teachers’ social-emotional talk from audio recordings in toddler classrooms could represent a transformative approach to help teachers better support children’s social-emotional development (e.g., understanding, managing, and expressing emotions). In turn, such a tool could better ensure young children gain the skills that ensure they are ready for school, relationships, and life. Project activities to demonstrate proof-of-concept for SEAL include: (1) developing a social and emotional word and phrase bank, informed by a national survey and focus groups with early childhood professionals and input from an expert advisory panel; (2) exploring teacher audio data to refine existing speech processing algorithms to detect classroom adult social emotional key words and phrases; and (3) examining initial validity of the word and phrase bank by comparing human transcription to a baseline algorithm to automatically detected speech data. This probe study serves to create evidence that a future fully formulated SEAL solution could yield data that will be easy to access and interpret and can be used by individual teachers, coaches, and early childhood programs to improve practices aimed at promoting child social emotional outcomes. Eventually, like an automated monitor for counting steps, we envision SEAL could be used by teachers themselves to monitor classroom social emotional talk and build capacity to improve social emotional competence in young children.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.