We describe the protocol used for collecting a corpus of conversational English speech from non-native speakers at several levels of proficiency, and report the results of preliminary automatic speech recognition (ASR) experiments on this corpus using HTK-based ASR systems. The speech corpus contains both read and conversational speech recorded simultaneously on wide-band and telephone channels, and has detailed time aligned transcriptions. The immediate goal of the ASR experiments is to assess the difficulty of the ASR problem in language learning exercises and thus to gauge how current ASR technology may be used in conversational computer assisted language learning (CALL) systems. The long-term goal of this research, of which the data collection and experiments are a first step, is to incorporate ASR into computer-based conversational language instruction systems.
Cite as: Byrne, W., Knodt, E., Khudanpur, S., Bernstein, J. (1998) Is automatic speech recognition ready for non-native speech? a data collection effort and initial experiments in modeling conversational Hispanic English. Proc. ETRW on Speech Technology in Language Learning (STiLL), 37-40
@inproceedings{byrne98_still,
author={William Byrne and Eva Knodt and Sanjeev Khudanpur and Jared Bernstein},
title={{Is automatic speech recognition ready for non-native speech? a data collection effort and initial experiments in modeling conversational Hispanic English}},
year=1998,
booktitle={Proc. ETRW on Speech Technology in Language Learning (STiLL)},
pages={37--40}
}