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For the purpose of developing pronunciation training tools for second language learning a corpus of non-native speech data has been collected, which consists of almost 18 hours of annotated speech signals spoken by Italian and German learners of English. The corpus is based on 250 utterances selected from typical second language learning exercises. It has(More)
Machine Readable Dictionaries (MRDs) have been used in a variety of language processing tasks including word sense disambiguation, text segmentation, information retrieval and information extraction. In this paper we describe the utilization of semantic knowledge acquired from an MRD for language modelling tasks in relation to speech recognition(More)
An automatic system for detection of pronunciation errors by adult learners of English is embedded in a lan-guage–learning package. Four main features are: (1) a recognizer robust to non–native speech; (2) localization of phone– and word–level errors; (3) diagnosis of what sorts of phone–level errors took place; and (4) a lexical– stress detector. These(More)
Arabic morphological analysers and stemming algorithms have become a popular area of research. Many computational linguists have designed and developed algorithms to solve the problem of morphology and stemming. Each researcher proposed his own gold standard, testing methodology and accuracy measurements to test and compute the accuracy of his algorithm.(More)
Within computational linguistics, the use of statistical pattern matching is generally restricted to speech processing. We have attempted to apply statistical techniques to discover a grammatical classification system from a Corpus of 'raw' English text. A discovery procedure is simpler for a simpler language model; we assume a first-order Markov model,(More)