Automatically Estimating Textual and Phonemic Complexity for Cued Speech: How to See the Sounds from French Texts

Abstract

In this position paper we present a methodology to automatically annotate French text for Cued Speech (CS), a communication system developed for people with hearing loss to complement speech reading at the phonetic level. This visual communication mode uses handshapes in different placements near the face in combination with the mouth movements (called ‘cues’ or ‘keys’) to make the phonemes of spoken language look different from each other. CS is used to acquire skills in lip reading, in oral communication and for reading. Despite many studies demonstrating its benefits, there are few resources available for learning and practicing it, especially in French. We thus propose a methodology to phonemize written corpora so that each word is aligned with the corresponding CS key(s). This methodology is proposed as part of a wider project aimed at creating an augmented reality system displaying a virtual coding hand where the user will be able to choose a text upon its complexity for cueing.

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