This paper describes the design, collection and current status of the Hans Christian Andersen (HCA) conversation corpus. The corpus consists of five separate corpora and represents transcription and annotation of some 57 hours of English spoken and deictic gesture user-system interaction recorded mainly with children 2002-2005. The corpora were collected as part of the development and evaluation process of two consecutive research prototypes. The set-up used to collect each corpus is described as well as our use of each corpus in system development. We describe the annotation of each corpus and briefly present various uses we have made of the corpora so far. The HCA corpus was made publicly available at http://www.niceproject.com/data/ in March 2006.

Many learning tasks require substantial skills training. Ideally, the student might benefit the most from having a human expert – a teacher or trainer – at hand throughout, but human expertise remains a scarce resource. The second-best solution could be to do skills training with a computer-based self-training system. This vision of the computer as tutor currently motivates increasing efforts world-wide, in all manner of fields, including that of computer-assisted language learning, or CALL. But, as pointed out by Hincks [2003], along with the growth of the CALL area comes a growing need for empirical evidence that CALL systems have a beneficial effect. This point is reiterated by Chapelle [2002] who defines the goal for Computer Assisted Second Language Research as the gathering of evidence for the effect of CALL and instructional design. This paper presents results of a field test of our pronunciation training system which enables immigrants and others to self-train their pronunciation skills of single Danish words.