DMCA
Data Driven Grammatical Error Detection in Transcripts of Children’s Speech
| Citations: | 1 - 0 self |
BibTeX
@MISC{Morley_datadriven,
author = {Eric Morley and Anna Eva Hallin and Brian Roark},
title = {Data Driven Grammatical Error Detection in Transcripts of Children’s Speech},
year = {}
}
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Abstract
We investigate grammatical error detec-tion in spoken language, and present a data-driven method to train a dependency parser to automatically identify and label grammatical errors. This method is ag-nostic to the label set used, and the only manual annotations needed for training are grammatical error labels. We find that the proposed system is robust to disfluencies, so that a separate stage to elide disfluen-cies is not required. The proposed system outperforms two baseline systems on two different corpora that use different sets of error tags. It is able to identify utterances with grammatical errors with an F1-score as high as 0.623, as compared to a baseline F1 of 0.350 on the same data. 1
Keyphrases
child speech data driven grammatical error detection proposed system grammatical error manual annotation grammatical error detec-tion baseline f1 dependency parser different set error tag label set separate stage grammatical error label baseline system different corpus data-driven method spoken language
