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Automatic Evaluation of Children Reading Aloud on Sentences and Pseudowords

2017-08-20Conference paper Open access
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dc.contributor.authorProença, Jorge
dc.contributor.authorLopes, Carla
dc.contributor.authorTjalve, Michael
dc.contributor.authorStolcke, Andreas
dc.contributor.authorCandeias, Sara
dc.contributor.authorPerdigão, Fernando
dc.date.accessioned2025-09-17T10:12:11Z
dc.date.available2025-09-17T10:12:11Z
dc.date.issued2017-08-20
dc.description.abstractReading aloud performance in children is typically assessed by teachers on an individual basis, manually marking reading time and incorrectly read words. A computational tool that assists with recording reading tasks, automatically analyzing them and providing performance metrics could be a significant help. Towards that goal, this work presents an approach to automatically predicting the overall reading aloud ability of primary school children (6-10 years old), based on the reading of sentences and pseudowords. The opinions of primary school teachers were gathered as ground truth of performance, who provided 0-5 scores closely related to the expectations at the end of each grade. To predict these scores automatically, features based on reading speed and number of disfluencies were extracted, after an automatic disfluency detection. Various regression models were trained, with Gaussian process regression giving best results for automatic features. Feature selection from both sentence and pseudoword reading tasks gave the closest predictions, with a correlation of 0.944. Compared to the use of manual annotation with the best correlation being 0.952, automatic annotation was only 0.8% worse. Furthermore, the error rate of predicted scores relative to ground truth was found to be smaller than the deviation of evaluators’ opinion per child.eng
dc.identifier.citationProença, Jorge & Lopes, Carla & Tjalve, Michael & Stolcke, Andreas & Candeias, Sara & Perdigão, Fernando. (2017). Automatic Evaluation of Children Reading Aloud on Sentences and Pseudowords. 2749-2753. 10.21437/Interspeech.2017-1541
dc.identifier.doi10.21437/interspeech.2017-1541
dc.identifier.urihttp://hdl.handle.net/10400.8/14081
dc.language.isoeng
dc.peerreviewedyes
dc.publisherISCA
dc.relation.ispartofInterspeech 2017
dc.rights.uriN/A
dc.subjectReading level assessment
dc.subjectChild speech
dc.subjectGaussian process regression
dc.titleAutomatic Evaluation of Children Reading Aloud on Sentences and Pseudowordseng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2017-08-20
oaire.citation.conferencePlaceStockholm, Sweden
oaire.citation.endPage2753
oaire.citation.startPage2749
oaire.citation.titleINTERSPEECH 2017
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85

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