Automatic measurement and analysis of the child verbal communication using classroom acoustics within a child care center
Automatic measurement and analysis of the child verbal communication using classroom acoustics within a child care center
复制标题
使用儿童保育中心内的教室声学自动测量和分析儿童言语交流
DOI：
--
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
J. Hansen
中科院分区：
文献类型：
--
作者：
M. Najafian;Dwight W. Irvin;Ying Luo;B. Rous;J. Hansen
了解早期学习者的语言环境对人类和机器来说都是一项具有挑战性的任务，它对于促进幼儿有效的语言发展至关重要。本文提出了现有diarization系统的一种新应用，并使用基于i向量基线的轮流策略来调查幼儿的语言环境，该策略捕获了托儿中心不同教室中成人对儿童或儿童对儿童的会话轮流。在对音频进行更深入的后续分析（如字数统计、语音识别和关键词识别）之前，检测说话人的转向是必要的，这有助于设计未来的学习空间，特别是为正常发育的儿童或有交流限制的儿童设计。在自然的儿童-教师课堂环境中进行的实验结果表明，在嘈杂的课堂条件下，所提出的儿童-成人快速言语转换方案非常有效，与LIUM diarization工具包产生的基线结果相比，相对错误率降低了27.3%。
Understanding the language environment of early learners is a challenging task for both human and machine, and it is critical in facilitating effective language development among young children. This papers presents a new application for the existing diarization systems and investigates the language environment of young children using a turn taking strategy employing an i-vector based baseline that captures adult-to-child or child-to-child conversational turns across different classrooms in a child care center. Detecting speaker turns is necessary before more in depth subsequent analysis of audio such as word count, speech recognition, and keyword spotting which can contribute to the design of future learning spaces specifically designed for typically developing children, or those at-risk with communication limitations. Experimental results using naturalistic child-teacher classroom settings indicate the proposed rapid child-adult speech turn taking scheme is highly effective under noisy classroom conditions and results in 27.3% relative error rate reduction compared to the baseline results produced by the LIUM diarization toolkit.