A Social Robot System for Modeling Children's Word Pronunciation: Socially Interactive Agents Track
A Social Robot System for Modeling Children's Word Pronunciation: Socially Interactive Agents Track
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用于模拟儿童单词发音的社交机器人系统：社交互动代理 Track
DOI：
10.5555/3237383.3237946
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
C. Breazeal
中科院分区：
文献类型：
--
作者：
Samuel Spaulding;Huili Chen;Safinah Ali;M. Kulinski;C. Breazeal
自主教育社交机器人可用于帮助提高幼儿的识字技能。这些机器人模仿人类教师的情感，感知和移情能力，能够复制人类教师一对一辅导的一些好处，部分原因是利用单个学生的行为和任务表现数据来推断他们知识的复杂模型。然后，这些学生模型用于提供个性化的教育体验，例如，确定课程材料的最佳顺序。在本文中，我们介绍了一个集成的系统，自主分析和评估儿童的语音和发音的背景下，互动的文字游戏之间的社会机器人和一个孩子。我们提出了一种新的游戏环境及其计算公式，用于实时捕获和分析儿童语音的集成管道，以及通过高斯过程回归（GPR）对儿童单词发音进行建模的自主机器人，增强主动学习协议，通知机器人的行为。我们表明，该系统是能够自主评估儿童的发音能力，与地面真理由人类评分员的实验后评估确定。我们还比较了音素和单词水平的GPR模型，并讨论了权衡每种方法在建模儿童的发音。最后，我们描述和分析了自动分析儿童的语音和发音的管道，包括SpeechAce作为自主，语音为基础的语言导师的未来发展的工具的评估。
Autonomous educational social robots can be used to help promote literacy skills in young children. Such robots, which emulate the emotive, perceptual, and empathic abilities of human teachers, are capable of replicating some of the benefits of one-on-one tutoring from human teachers, in part by leveraging individual student's behavior and task performance data to infer sophisticated models of their knowledge. These student models are then used to provide personalized educational experiences by, for example, determining the optimal sequencing of curricular material. In this paper we introduce an integrated system for autonomously analyzing and assessing children's speech and pronunciation in the context of an interactive word game between a social robot and a child. We present a novel game environment and its computational formulation, an integrated pipeline for capturing and analyzing children's speech in real-time, and an autonomous robot that models children's word pronunciation via Gaussian Process Regression (GPR), augmented with an Active Learning protocol that informs the robot's behavior. We show that the system is capable of autonomously assessing children's pronunciation ability, with ground truth determined by a post-experiment evaluation by human raters. We also compare phoneme- and word-level GPR models and discuss trade-offs of each approach in modeling children's pronunciation. Finally, we describe and analyze a pipeline for automatic analysis of children's speech and pronunciation, including an evaluation of SpeechAce as a tool for future development of autonomous, speech-based language tutors.
西班牙语学龄前儿童的双语和读写能力发展。
影响因子：
3
作者：
Páez,MarielaM;Tabors,PattonO;López,LisaM
通讯作者：
López,LisaM