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        <title>Predicting Multidimensional Subjective Ratings of Children’ Readings from the Speech Signals for the Automatic Assessment of Fluency</title>
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        <namePart type="given">Gérard</namePart>
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        <namePart type="given">Erika</namePart>
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    <name type="personal">
        <namePart type="given">Anne-Laure</namePart>
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    <name type="personal">
        <namePart type="given">Marie-Line</namePart>
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    <abstract>The objective of this research is to estimate multidimensional subjective ratings of the reading performance of young readers from signal-based objective measures. We here combine linguistic features (number of correct words, repetitions, deletions, insertions uttered per minute . . . ) with phonetic features. Expressivity is particularly difficult to predict since there is no unique golden standard. We here propose a novel framework for performing such an estimation that exploits multiple references performed by adults and demonstrate its efficiency using recordings of 273 pupils.</abstract>
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%0 Conference Proceedings
%T Predicting Multidimensional Subjective Ratings of Children’ Readings from the Speech Signals for the Automatic Assessment of Fluency
%A Bailly, Gérard
%A Godde, Erika
%A Piat-Marchand, Anne-Laure
%A Bosse, Marie-Line
%S Proceedings of the Twelfth Language Resources and Evaluation Conference
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G English
%F bailly-etal-2020-predicting
%X The objective of this research is to estimate multidimensional subjective ratings of the reading performance of young readers from signal-based objective measures. We here combine linguistic features (number of correct words, repetitions, deletions, insertions uttered per minute . . . ) with phonetic features. Expressivity is particularly difficult to predict since there is no unique golden standard. We here propose a novel framework for performing such an estimation that exploits multiple references performed by adults and demonstrate its efficiency using recordings of 273 pupils.
%U https://aclanthology.org/2020.lrec-1.39
%P 317-322

Markdown (Informal)

[Predicting Multidimensional Subjective Ratings of Children’ Readings from the Speech Signals for the Automatic Assessment of Fluency](https://aclanthology.org/2020.lrec-1.39) (Bailly et al., LREC 2020)

• Predicting Multidimensional Subjective Ratings of Children’ Readings from the Speech Signals for the Automatic Assessment of Fluency (Bailly et al., LREC 2020)

ACL

• Gérard Bailly, Erika Godde, Anne-Laure Piat-Marchand, and Marie-Line Bosse. 2020. Predicting Multidimensional Subjective Ratings of Children’ Readings from the Speech Signals for the Automatic Assessment of Fluency. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 317–322, Marseille, France. European Language Resources Association.