The ISLE Corpus of Non-Native Spoken English

Abstract

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 been annotated at the word and the phone level, to highlight pronunciation errors such as phone realisation problems and misplaced word stress assignments. The data has been used to develop and evaluate several diagnostic components, which can be used to produce corrective feedback of unprecedented detail to a language learner. 1 This research has been supported by the European Commission under the 4 th framework of the Telematics Application Programme (Language Engineering Project LE4-8353). Introduction Project ISLE (Interactive Spoken Language Education) has the goal of integrating state-of-the-art Hidden Markov Model [HMM] ...