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        <title>Towards a Standardized, Fine-grained Manual Annotation Protocol for Verbal Fluency Data</title>
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    <name type="personal">
        <namePart type="given">Gabriel</namePart>
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    <name type="personal">
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            <title>Proceedings of the 14th Linguistic Annotation Workshop</title>
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            <namePart type="given">Stefanie</namePart>
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    <abstract>We propose a new method for annotating verbal fluency data, which allows the reliable detection of the age-related decline of lexical access capacity. The main innovation is that annotators should inferentially assess the intention of the speaker when producing a word form during a verbal fluency test. Our method correlates probable speaker inten-tions such as “intended as a valid answer” or “intended as a meta-comment” with lin-guistic features such as word intensity (e.g. reduced intensity suggests private speech) and syntactic integration. The annotation scheme can be implemented with high reliabil-ity, and minimal linguistic training. When fluency data are annotated using this scheme, a relation between fluency and age emerges; this is in contrast to a strict implementation of the traditional method of annotating verbal fluency data, which has no way of deal-ing with score-confounding phenomena because it force-groups all verbal fluency pro-ductions –regardless of speaker intention— into one of three taxonomic groups (i.e. val-id answers, perseverations, and intrusions). The traditional lack of fine-grained annota-tion units is especially problematic when analyzing the qualitatively distinct fluency da-ta of older participants and may cause studies to miss the relation between lexical access capacity and age.</abstract>
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%0 Conference Proceedings
%T Towards a Standardized, Fine-grained Manual Annotation Protocol for Verbal Fluency Data
%A McKee, Gabriel
%A Macoir, Joël
%A Gagnon, Lydia
%A Tremblay, Pascale
%Y Dipper, Stefanie
%Y Zeldes, Amir
%S Proceedings of the 14th Linguistic Annotation Workshop
%D 2020
%8 December
%I Association for Computational Linguistics
%C Barcelona, Spain
%F mckee-etal-2020-towards
%X We propose a new method for annotating verbal fluency data, which allows the reliable detection of the age-related decline of lexical access capacity. The main innovation is that annotators should inferentially assess the intention of the speaker when producing a word form during a verbal fluency test. Our method correlates probable speaker inten-tions such as “intended as a valid answer” or “intended as a meta-comment” with lin-guistic features such as word intensity (e.g. reduced intensity suggests private speech) and syntactic integration. The annotation scheme can be implemented with high reliabil-ity, and minimal linguistic training. When fluency data are annotated using this scheme, a relation between fluency and age emerges; this is in contrast to a strict implementation of the traditional method of annotating verbal fluency data, which has no way of deal-ing with score-confounding phenomena because it force-groups all verbal fluency pro-ductions –regardless of speaker intention— into one of three taxonomic groups (i.e. val-id answers, perseverations, and intrusions). The traditional lack of fine-grained annota-tion units is especially problematic when analyzing the qualitatively distinct fluency da-ta of older participants and may cause studies to miss the relation between lexical access capacity and age.
%U https://aclanthology.org/2020.law-1.15
%P 160-166

Markdown (Informal)

[Towards a Standardized, Fine-grained Manual Annotation Protocol for Verbal Fluency Data](https://aclanthology.org/2020.law-1.15) (McKee et al., LAW 2020)

• Towards a Standardized, Fine-grained Manual Annotation Protocol for Verbal Fluency Data (McKee et al., LAW 2020)

ACL

• Gabriel McKee, Joël Macoir, Lydia Gagnon, and Pascale Tremblay. 2020. Towards a Standardized, Fine-grained Manual Annotation Protocol for Verbal Fluency Data. In Proceedings of the 14th Linguistic Annotation Workshop, pages 160–166, Barcelona, Spain. Association for Computational Linguistics.