Papers by Brigitte Bigi
Automatically Estimating Textual and Phonemic Complexity for Cued Speech: How to See the Sounds from French Texts (2024.lrec-main)
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| Challenge: | Cued Speech (CS) is a visual communication system developed for people with hearing loss to complement speech reading at the phonetic level. |
| Approach: | They propose a method to phonemize written corpora so that each word is aligned with the corresponding CS key(s) this method is 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. |
| Outcome: | The proposed method is part of a wider project aimed at creating an augmented reality system displaying a virtual coding hand where the user can choose a text upon its complexity for cueing. |
CLeLfPC: a Large Open Multi-Speaker Corpus of French Cued Speech (2022.lrec-1)
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| Challenge: | Cued Speech is a visual communication system developed for deaf people to complement speechreading at the phonetic level with hands. |
| Approach: | They describe a visual communication mode that uses handshapes in different placements near the face and mouth movements to make the phonemes of spoken language look different from each other. |
| Outcome: | The proposed system is based on 4 hours of audio and video recordings of 23 participants. |
Multimodal Corpus of Bidirectional Conversation of Human-human and Human-robot Interaction during fMRI Scanning (2020.lrec-1)
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Birgit Rauchbauer, Youssef Hmamouche, Brigitte Bigi, Laurent Prévot, Magalie Ochs, Thierry Chaminade
| Challenge: | a study of real-life bi-directional conversations combines multimodal corpus with neural, physiological and behavioral data. |
| Approach: | They propose a multimodal corpus derived from natural conversations . they used human-human interactions as a control condition . |
| Outcome: | The proposed corpus includes neural, physiological and behavioral data. |
Developing Resources for Automated Speech Processing of Quebec French (2020.lrec-1)
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| Challenge: | acoustic models for automatic segmentation of Quebec French are not available for all languages . linguistic resources are developed to perform phonetic annotations in Quebec French . physical characteristics of speech can be observed in the production of sounds . |
| Approach: | They propose to use a French lexicon to train automatic QF segmentation models . they adapt existing pronunciation dictionary and acoustic model from existing ones . |
| Outcome: | The proposed tools perform the full process of speech segmentation in Quebec French. |
“Cheese!”: a Corpus of Face-to-face French Interactions. A Case Study for Analyzing Smiling and Conversational Humor (2020.lrec-1)
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| Challenge: | Cheese! is a conversational corpus containing 11 mixed and non-mixed dyadic interactions lasting around 15 minutes each. |
| Approach: | They propose to use a conversational corpus to compare smiling behavior in American English and French conversations to conduct a cross-cultural comparison. |
| Outcome: | The proposed study examines the relationship between smile and humor in conversational interactions between American English and French participants. |