Non-native English speakers' speech correction, based on domain focused document

With the increase in exchange programs, many international students worldwide can face communication problems. During lectures, usually English language is used for the communication between students and teachers. However both sides, not necessarily being native speakers of English, may misunderstand each other. In this paper we propose a method for correction of non-native English speakers' speech, based on the domain focused electronic document. The method relies on the results of speech recognition (SR) software, and uses them altogether with the document. Our approach consists of three steps. Firstly, document analysis in the preprocessing phase. Secondly, finding the document part corresponding to sentence from SR software, realised using the Hidden Markov Model (HMM) based method. Finally, the correction by calculating the score for each of candidate sentences, based on the result of SR software. The probability score combines keywords comparison, BM25F method and HMM based method scores. Highest score candidate is chosen as replacement.