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Concurrent Speech Synthesis to Improve Document First Glance for the Blind

Fabrice Maurel 1 Gaël Dias 1 Stéphane Ferrari 1 Judith-Jeyafreeda Andrew Emmanuel Giguet 1 
1 Equipe Hultech - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image et Instrumentation de Caen
Abstract : Skimming and scanning are two well-known reading processes, which are combined to access the document content as quickly and efficiently as possible. While both are available in visual reading mode, it is rather difficult to use them in non visual environments because they mainly rely on typographical and layout properties. In this article, we introduce the concept of tag thunder as a way (1) to achieve the oral transposition of the web 2.0 concept of tag cloud and (2) to produce an innovative interactive stimulus to observe the emergence of self-adapted strategies for non-visual skimming of written texts. We first present our general and theoretical approach to the problem of both fast, global and non-visual access to web browsing; then we detail the progress of development and evaluation of the various components that make up our software architecture. We start from the hypothesis that the semantics of the visual architecture of web pages can be transposed into new sensory modalities thanks to three main steps (web page segmentation, keywords extraction and sound spatialization). We note the difficulty of simultaneously (1) evaluating a modular system as a whole at the end of the processing chain and (2) identifying at the level of each software brick the exact origin of its limits; despite this issue, the results of the first evaluation campaign seem promising.
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Submitted on : Wednesday, October 9, 2019 - 2:23:27 PM
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Fabrice Maurel, Gaël Dias, Stéphane Ferrari, Judith-Jeyafreeda Andrew, Emmanuel Giguet. Concurrent Speech Synthesis to Improve Document First Glance for the Blind. 2nd International Workshop on Human-Document Interaction (HDI 2019) in conjunction with IAPR/IEEE ICDAR 2019, Sep 2019, Sydney, Australia. ⟨hal-02309647⟩

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