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    <abstract>A framework is proposed for the detection of reduplication in digital videos of American Sign Language (ASL). In ASL, reduplication is used for a variety of linguistic purposes, including overt marking of plurality on nouns, aspectual inflection on verbs, and nominalization of verbal forms. Reduplication involves the repetition, often partial, of the articulation of a sign. In this paper, the apriori algorithm for mining frequent patterns in data streams is adapted for finding reduplication in videos of ASL. The proposed algorithm can account for varying weights on items in the apriori algorithm’s input sequence. In addition, the apriori algorithm is extended to allow for inexact matching of similar hand motion subsequences and to provide robustness to noise. The formulation is evaluated on 105 lexical signs produced by two native signers. To demonstrate the formulation, overall hand motion direction and magnitude are considered; however, the formulation should be amenable to combining these features with others, such as hand shape, orientation, and place of articulation.</abstract>
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%0 Conference Proceedings
%T Detecting Reduplication in Videos of American Sign Language
%A Gavrilov, Zoya
%A Sclaroff, Stan
%A Neidle, Carol
%A Dickinson, Sven
%S Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC’12)
%D 2012
%8 may
%I European Language Resources Association (ELRA)
%C Istanbul, Turkey
%F gavrilov-etal-2012-detecting
%X A framework is proposed for the detection of reduplication in digital videos of American Sign Language (ASL). In ASL, reduplication is used for a variety of linguistic purposes, including overt marking of plurality on nouns, aspectual inflection on verbs, and nominalization of verbal forms. Reduplication involves the repetition, often partial, of the articulation of a sign. In this paper, the apriori algorithm for mining frequent patterns in data streams is adapted for finding reduplication in videos of ASL. The proposed algorithm can account for varying weights on items in the apriori algorithm’s input sequence. In addition, the apriori algorithm is extended to allow for inexact matching of similar hand motion subsequences and to provide robustness to noise. The formulation is evaluated on 105 lexical signs produced by two native signers. To demonstrate the formulation, overall hand motion direction and magnitude are considered; however, the formulation should be amenable to combining these features with others, such as hand shape, orientation, and place of articulation.
%U http://www.lrec-conf.org/proceedings/lrec2012/pdf/199_Paper.pdf
%P 3767-3773

Markdown (Informal)

[Detecting Reduplication in Videos of American Sign Language](http://www.lrec-conf.org/proceedings/lrec2012/pdf/199_Paper.pdf) (Gavrilov et al., LREC 2012)

• Detecting Reduplication in Videos of American Sign Language (Gavrilov et al., LREC 2012)

ACL

• Zoya Gavrilov, Stan Sclaroff, Carol Neidle, and Sven Dickinson. 2012. Detecting Reduplication in Videos of American Sign Language. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 3767–3773, Istanbul, Turkey. European Language Resources Association (ELRA).