Show simple item record

dc.contributor.authorLu, Yitingen
dc.contributor.authorGales, Marken
dc.contributor.authorKnill, Katherineen
dc.contributor.authorManakul, Potsaweeen
dc.contributor.authorWang, Len
dc.contributor.authorWang, Yen
dc.date.accessioned2019-07-26T23:30:35Z
dc.date.available2019-07-26T23:30:35Z
dc.date.issued2019-01-01en
dc.identifier.issn2308-457X
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/295000
dc.description.abstractComputer assisted language learning (CALL) systems aidlearners to monitor their progress by providing scoring andfeedback on language assessment tasks. Free speaking tests al-low assessment of what a learner has said, as well as how theysaid it. For these tasks, Automatic Speech Recognition (ASR)is required to generate transcriptions of a candidate’s responses,the quality of these transcriptions is crucial to provide reliablefeedback in downstream processes. This paper considers theimpact of ASR performance on Grammatical Error Detection(GED) for free speaking tasks, as an example of providing feed-back on a learner’s use of English. The performance of an ad-vanced deep-learning based GED system, initially trained onwritten corpora, is used to evaluate the influence of ASR errors.One consequence of these errors is that grammatical errors canresult from incorrect transcriptions as well as learner errors, thismay yield confusing feedback. To mitigate the effect of theseerrors, and reduce erroneous feedback, ASR confidence scoresare incorporated into the GED system. By additionally adaptingthe written text GED system to the speech domain, using ASRtranscriptions, significant gains in performance can be achieved.Analysis of the GED performance for different grammatical er-ror types and across grade is also presented.
dc.description.sponsorshipALTA
dc.rightsAll rights reserved
dc.rights.uri
dc.titleImpact of ASR performance on spoken grammatical error detectionen
dc.typeConference Object
prism.endingPage1880
prism.publicationDate2019en
prism.publicationNameProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECHen
prism.startingPage1876
prism.volume2019-Septemberen
dc.identifier.doi10.17863/CAM.42081
dcterms.dateAccepted2019-06-28en
rioxxterms.versionofrecord10.21437/Interspeech.2019-1706en
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2019-01-01en
dc.contributor.orcidGales, Mark [0000-0002-5311-8219]
dc.contributor.orcidKnill, Katherine [0000-0003-1292-2769]
dc.contributor.orcidManakul, Potsawee [0000-0001-7108-8626]
dc.identifier.eissn1990-9772
rioxxterms.typeConference Paper/Proceeding/Abstracten
pubs.funder-project-idCambridge Assessment (unknown)
cam.orpheus.successThu Nov 05 11:54:23 GMT 2020 - Embargo updated*
rioxxterms.freetoread.startdate2020-01-01


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record