The pedagogical effectiveness of ASR-based computer assisted pronunciation training
In case you object to the disclosure of your thesis, you can contact email@example.com
S.l. : s.n.
Number of pages
XVI, 182 p.
Radboud Universiteit Nijmegen, 08 juni 2007
Promotor : Boves, L.W.J. Co-promotores : Cucchiarini, C., Strik, H.
Display more detailsDisplay less details
CLST - Centre for Language and Speech Technology
SubjectLinguistic Information Processing; Implicaties van potentieel foutieve feedback van call-systemen (Call = computer assisted language learning)
Computer Assisted Pronunciation Training (CAPT) systems with Automatic Speech Recognition (ASR) technology have become increasingly popular to train pronunciation in the second language (L2). The advantage of these systems is the provision of a self-paced, stress-free type of training with automatic feedback on pronunciation quality. Despite this popularity, little is known on the actual pedagogical effectiveness of these systems. In other words, little empirical evidence is available as to whether and to what extent the use of these systems can improve pronunciation quality for a learner, while it is well-known that ASR-based feedback on non-native pronunciation quality is not yet 100% error-free. The research reported on in this thesis investigates the pedagogical effectiveness of ASR-based feedback on segmental quality. The thesis starts by identifying pedagogical requirements for pronunciation training in L2. Existing CAPT systems are then critically examined to establish which pedagogical requirements can be achieved with current ASR-based CAPT technology. Some of these suggestions are subsequently implemented to develop a customized ASR-based CAPT system (Dutch-CAPT) for teaching Dutch pronunciation to adult immigrants. First, a method is presented to select important segmental errors made by learners of Dutch with different mother tongues. By means of auditory analyses of different speech databases, an inventory of eight Dutch phonemes that appear to be particularly problematic tp learn is obtained. This inventory is subsequently implemented in Dutch-CAPT, which offers a simple form of feedback on segmental errors. The improvement made by a group of immigrants who used Dutch-CAPT is measured and compared to that of controls. The results indicate that the ASR-based feedback provided yielded the largest improvements in the pronunciation of the targeted phonemes, despite occasional errors in the feedback. The thesis ends with suggestions to design pedagogically sound and technologically reliable ASR-based CAPT, and to evaluate these systems
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.