It is argued that language learning is regarded as the cornerstone of human existence. The widespread use of English as an international language makes it highly important in the world. It is no more working as the status of language of the elite class or the educated class of the society such as professors, rather it is working as an instrument to bring success in life. Nowadays, teachers need...

This paper describes the development of the Wildcat Corpus of native- and foreign-accented English,a corpus containing scripted and spontaneous speech recordings from 24 native speakers of American English and 52 non-native speakers of English.The core element of this corpus is a set of spontaneous speech recordings, for which a new method of eliciting dialogue-based, laboratory-quality speech ...

<p class="abstrak">This study explores the roles of Non-Native English Speaking Teachers (NNESTs) in facilitating improvement participants' speaking skills. The research was prompted by challenge faced a NNESTs from Indonesia, who relocated to Kyrgyzstan teach as second language. teacher lacked cultural knowledge support his language learning. To address this, employed descriptive qualita...

This paper proposes the automatic generation of Fill-in-the-Blank Questions (FBQs) together with testing based on Item Response Theory (IRT) to measure English proficiency. First, the proposal generates an FBQ from a given sentence in English. The position of a blank in the sentence is determined, and the word at that position is considered as the correct choice. The candidates for incorrect ch...

This paper presents and evaluates approaches to automatically score the content correctness of spoken responses in a new language test for teachers of English as a foreign language who are non-native speakers of English. Most existing tests of English spoken proficiency elicit responses that are either very constrained (e.g., reading a passage aloud) or are of a predominantly spontaneous nature...

This paper describes MITRE’s participation in the native language identification (NLI) task at BEA-8. Our best effort performed at an accuracy of 82.6% in the eleven-way NLI task, placing it in a statistical tie with the best performing systems. We describe the variety of machine learning approaches that we explored, including Winnow, language modeling, logistic regression and maximum-entropy m...

Grammatical error correction (GEC) is the task of automatically correcting grammatical errors in written text. Previous research has mainly focussed on individual error types and current commercial proofreading tools only target limited error types. As sentences produced by learners may contain multiple errors of different types, a practical error correction system should be able to detect and ...