A method is presented for performing speech recognition that is not dependent on a fixed word vocabulary. Particles are used as the recognition units in a speech recognition system which permits word-vocabulary independent speech decoding. A particle represents a concatenated phone sequence. Each string of particles that represents a word in the one-best hypothesis from the particle speech reco...

Two main features of vocabulary knowledge, namely breadth and depth, have a fundamental role in vocabulary research. This research aimed to study the relationship between vocabulary knowledge and reading comprehension, and to investigate which feature of vocabulary knowledge, breadth or depth, had better impact on identifying reading comprehension performance. Therefore, three language tests we...

this study has examined the effect of semantic mapping on learning vocabulary across genders. the researchers selected 120 intermediate students after the administration of a standard proficiency test. a vocabulary test was also used to measure the students’ vocabulary knowledge. the experimental group received semantic mapping in the pre-reading stage, butthe control group did not receive this...

To federate collections with varying degrees of metadata richness across continents poses a number of challenging issues such as: how to build a rich unified search interface when there is a lack of controlled vocabulary, and how to federate collections in different languages. The focus of this paper is on the approaches we have taken to address these issues in Arc, an OAI compliant federated d...

The present study investigated the potential of writing in English as a foreign language (EFL) for learning by manipulating cognitive task complexity based on related models and hypotheses. essays written 59 Chinese postgraduate EFL students from different subject areas were analysed with reference to complexity, accuracy, fluency (CAF). Results showed that had no significant effect learners’ l...

Tracking a digital pursuit rotor task was used to measure dual task costs of language production by young and older adults. Tracking performance by both groups was affected by dual task demands: time on target declined and tracking error increased as dual task demands increased from the baseline condition to a moderately demanding dual task condition to a more demanding dual task condition. Whe...

Neural machine translation (NMT), a new approach to machine translation, has achieved promising results comparable to those of traditional approaches such as statistical machine translation (SMT). Despite its recent success, NMT cannot handle a larger vocabulary because training complexity and decoding complexity proportionally increase with the number of target words. This problem becomes even...