The main aim of this study is to investigate if verbal, vocal and facial information can be used to identify low-engaged second language learners in robot-led conversation practice. The experiments were performed on voice recordings and video data from 50 conversations, in which a robotic head talks with pairs of adult language learners using four different interaction strategies with varying robot-learner focus and initiative. It was found that these robot interaction strategies influenced learner activity and engagement. The verbal analysis indicated that learners with low activity rated the robot significantly lower on two out of four scales related to social competence. The acoustic vocal and video-based facial analysis, based on manual annotations or machine learning classification, both showed that learners with low engagement rated the robot’s social competencies consistently, and in several cases significantly, lower, and in addition rated the learning effectiveness lower. The agreement between manual and automatic identification of low-engaged learners based on voice recordings or face videos was further found to be adequate for future use. These experiments constitute a first step towards enabling adaption to learners’ activity and engagement through within- and between-strategy changes of the robot’s interaction with learners. ; QC 20211202


    Access

    Download


    Export, share and cite



    Title :

    Identification of low-engaged learners in robot-led second language conversations with adults


    Contributors:

    Type of media :

    Paper


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    420 / 629



    Is a wizard-of-Oz required for robot-led conversations in a second language?

    Engwall, Olov / Águas Lopes, José David / Cumbal, Ronald | BASE

    Free access


    CONVERSATIONS

    Bahcall, John | Online Contents | 1998


    CONVERSATIONS

    Condit, Philip | Online Contents | 1997


    CONVERSATIONS

    Online Contents | 1997