As speech recognition systems improve in quality, they become attractive as components in applications which will be used by non-native speakers, both applications designed speciically for language learners and those intended for general use. Recognizer performance on speakers who are not uent in the language they are speaking, however, is often poor. A number of factors contribute to recogniti...

This study aims to examine the cross-cultural similarities and differences in the use of rapport management strategies (rapport enhancement, rapport maintenance, rapport neglect, and rapport challenge) in the complaints during service encounters based on Spencer Oatey’s (2008) model. To this end, 90 participants (30 Persian native speakers, 30 Iranian EFL (English as a foreign language) learner...

In this study, we compare the effects of English lexical features on word duration for native and non-native English speakers and for non-native speakers with different L1s and a range of L2 experience. We also examine whether non-native word durations lead to judgments of a stronger foreign accent. We measured word durations in English paragraphs read by 12 American English (AE), 20 Korean, an...

Native speakers of non-tonal languages, such as American English, frequently have difficulty accurately producing the tones of Mandarin Chinese. This paper describes a corpus of Mandarin Chinese spoken by non-native speakers and annotated for tone quality using a simple good/bad system. We examine interrater correlation of the annotations and highlight the differences in feature distribution be...

Automatic speech recognition (ASR) technology has achieved a level of maturity, where it is already practical to be used by novice users. However, most non-native speakers are still not comfortable with services including ASR systems, because of the accuracy on non-native speakers. This paper describes our approach in constructing a non-native corpus particularly in French for testing and adapt...

At present, the population of non-native speakers is twice that of native speakers. It is necessary to explore the text generation strategies for non-native users. However, little has been done in this field. This study investigates the features that affect the placement (where to place a cue) of because for non-native speakers. A machine learning program – C4.5 was applied to induce the classi...