The development of our ICALL system is supported by the Incomplete Grammar approach, which allows us to model the learner with a cognitively based system of hypotheses held by the Tutor module. An Incomplete Grammar model of a learner’s language performance includes Constituent Productions PC, Constituent Production Errors PCE , Lexical Productions PCL and Lexical Production Errors PLE in the l...

Inner speech, that little voice that people often hear inside their heads while thinking, is a form of mental imagery. The properties of inner speech errors can be used to investigate the nature of inner speech, just as overt slips are informative about overt speech production. Overt slips tend to create words (lexical bias) and involve similar exchanging phonemes (phonemic similarity effect). ...

This paper describes the application of the Momel algorithm to a corpus of spontaneous speech in Standard (Beijing) Chinese. A selection of utterances by four speakers was analysed automatically and the resynthesised utterances were evaluated subjectively with two categories of errors: lexical tone errors and intonation errors. The target points determining the pitch contours of the synthetic u...

We report the naming performance of a patient (DM) with a fluent progressive aphasia who made phonological errors in all language production tasks. The pattern of errors in naming was strikingly clear: DM made very many phonological errors that resulted almost always in nonword responses. The complete absence of semantic errors and the very low ratio of formal errors relative to nonword errors ...

& Lexical proficiency, as a cognitive construct, is poorly understood. However, lexical proficiency is an important element of language proficiency and fluency, especially for second language (L2) learners. For example, lexical errors are a common cause of L2 miscommunication (Ellis, 1995). Lexical proficiency is also an important attribute of L2 academic achievement (Daller, van Hout, & Treffe...

Single word production requires that phoneme activation is maintained while articulatory conversion is taking place. Word serial recall, connected speech and non-word production (repetition and spelling) are all assumed to involve a phonological output buffer. A crucial question is whether the same memory resources are also involved in single word production. We investigate this question by ass...

This demonstration presents de-stress: the German (de) System for Training and Research on Errors in Second-language Stress [1]. This prototype Computer-Assisted Pronunciation Training (CAPT) tool provides a variety of options for diagnosis of and feedback on lexical stress errors, and could potentially be a useful component of an intelligent CAPT system.

This paper describes a method of detecting grammatical and lexical errors made by Japanese learners of English and other techniques that improve the accuracy of error detection with a limited amount of training data. In this paper, we demonstrate to what extent the proposed methods hold promise by conducting experiments using our learner corpus, which contains information on learners’ errors.