In this paper, we present an overview of the RWTH Aachen large vocabulary continuous speech recognizer. The recognizer is based on continuous density hidden Markov models and a time-synchronous left-to-right beam search strategy. Experimental results on the ARPA Wall Street Journal (WSJ) corpus verify the effects of several system components, namely linear discriminant analysis, vocal tract nor...

This study aimed to investigate the effect of using vocabulary software on the vocabulary learning of Iranian EFL learners. Participants of the study were 54 intermediate-level students (23 males and 31 females) learning English as a foreign language in Mehr Institute in Izeh who were selected after taking the Nelson English Language Test as a proficiency test. They were randomly divided into t...

Specifics of hidden Markov model-based speech recognition are investigated. Influence of modeling simple and context-dependent phones, using simple Gaussian, two and threecomponent Gaussian mixture probability density functions for modeling feature distribution, and incorporating language model are discussed. Word recognition rates and model complexity criteria are used for evaluating suitabili...

This study investigated the impact of semantic clustering on Iranian EFL learners’ vocabulary retention at advanced level. Participants were female learners randomly assigned to two groups of 15. Four instruments (TOEFL test; vocabulary pretest; immediate posttest, and delayed recall posttest) were used. The experimental group underwent semantic clustering vocabulary presentation in which the l...

This study investigated the amount of incidental vocabulary learning through comprehension-focused reading of short stories and explicit instruction to this goal.  Forty male high school students were selected randomly, and divided into two groups of twenty.  One group of these students was given five 400-word-level short stories to read with the purpose of comprehension, and the students in th...