Automated Corrective Feedback in the Context of ASR-supported Pronunciation Training: how effective can it be?

Recently, Web 2.0 and mobile applications have become an endless source of new technological tools that integrate Automatic Speech Recognition (ASR). Their use in learning environments has led to a growing interest by researchers whose studies demonstrate the effectiveness of these new tools in relation to acquiring L2 pronunciation, to developing oral proficiency in general, and to providing instantaneous individualized feedback (Strik et al. 2009, 2012; Cucchiarini & Strik, 2013, Liakin et al. 2015, 2017).

In this presentation, we will first examine different types of implicit and explicit corrective feedback that ASR-based applications can provide and will discuss their impact on the acquisition of L2 pronunciation in light of SLA findings (Lyster 1998, 2004; Ellis et al., 2006; Lee & Lyster, 2016 among others). Second, we will report the results of our action research on the use of three different ASR-based tools in two university-level French pronunciation courses, with specific reference to learners’ perceptions of the utility of different types of automatic corrective feedback provided by these applications.To conclude, we will offer avenues of discussion and practical suggestions for the effective and sensible integration of ASR-based applications in the teaching and learning of L2 pronunciation, in and beyond the classroom.