Spoken grammar practice and feedback in an ASR-based CALL system

Abstract

Speaking practice is important for learners of a second language. Computer assisted language learning (CALL) systems can provide attractive opportunities for speaking practice when combined with automatic speech recognition (ASR) technology. In this paper, we present a CALL system that offers spoken practice of word order, an important aspect of Dutch grammar. The system uses ASR technology to process the learner's responses and to detect errors so that immediate corrective feedback (CF) can be provided on learner errors. We evaluate the system as a learning environment by analyzing proficiency gains in pre-and post-tests, the logs of the practice sessions, and the learners' appreciation of the system. In this paper, we present two learning conditions: (1) the learners received oral practice and immediate CF on spoken performance and (2) learners received oral practice and NO CF on spoken performance. We found that our system was successful in providing L2 speaking practice. Results show that both groups improve their proficiency on the target feature as a result of treatment. Between the groups there is no significant difference in learning, but the groups proceeded differently through the sessions, and the learners in the group that received automatic CF evaluated the system more positively than the NO CF group. We discuss the performance of the system as an environment for language learning and the obtained proficiency test results, and relate them to current views on second language acquisition.

Review of Studies on Technology-Enhanced Language Learning and Teaching

“…SR has great potential for providing feedback, so it is combined with automatic correction and feedback (ACF) technology, so that students can develop more autonomous pronunciation [68]. Scholars [69] proposed a system to provide oral practice of word order. The system used SR technology to process learners' responses and to detect errors in order to provide immediate corrective feedback on learners' errors.…”

Impact of ASR Performance on Spoken Grammatical Error Detection

“…In [2] a rulebased grammatical error collection system was proposed which is tailored to a subset of error types. For non-spontaneous speech, [3] proposed a grammatical error detection (GED) system comparing a candidate's answer to a matching reference focused on a question-answering style test. By contrast, in recent years significant developments have been achieved in detecting This paper reports on research supported by Cambridge Assessment, University of Cambridge.…”

Una aproximación del efecto en el aprendizaje de una lengua extranjera debida a la obtención de datos a través de exámenes en línea de idiomas

“…El desarrollo de entornos de aprendizaje adaptativos puede ayudar a los agentes educativos (profesores, alumnos, instituciones, etc…) a conocer, mejorar y personalizar el escenario formativo de un área concreta de conocimiento, (Bailin, 1988;Harrington, 1996;Robinson, 2005;Dodigovic, 2007;Ettlinger, Morgan-Short, Faretta-Stutenberg, & Wong, 2016). El procesamiento de datos generados por el usuario sobre un entorno de aprendizaje puede generar formulas predictivas que ayude a mejorar las estrategias de aprendizaje educativas de carácter semiautomático (Luckin et Al., 2016) o simplemente orientar cómo mejorar su actuación especialmente en la lengua hablada (Neri, Cucchiarini, & Strik, 2008;de Vries, Cucchiarini, Bodnar, Strik, & van Hout, 2015).…”