CHEESE! : Corpus « CHEESE! »

Priego-Valverde, Béatrice; Bigi, Brigitte; Amoyal, Mary

doi:10.4000/tipa.5525

Cited by 2 publications

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“…For a larger amount of data, we employ additionally the Cheese dataset [55], selecting 10 interaction scenes involving free conversation of students, in French. We chose this dataset because it also contains interaction scenes.…”

Section: Selected Datasetsmentioning

confidence: 99%

Towards the generation of synchronized and believable non-verbal facial behaviors of a talking virtual agent

Delbosc,

Ochs,

Sabouret

et al. 2023

International Cconference on Multimodal Interaction

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This paper introduces a new model to generate rhythmically relevant non-verbal facial behaviors for virtual agents while they speak. The model demonstrates perceived performance comparable to behaviors directly extracted from the data and replayed on a virtual agent, in terms of synchronization with speech and believability. Interestingly, we found that training the model with two different sets of data, instead of one, did not necessarily improve its performance. The expressiveness of the people in the dataset and the shooting conditions are key elements. We also show that employing an adversarial model, in which fabricated fake examples are introduced during the training phase, increases the perception of synchronization with speech. A collection of videos demonstrating the results and code can be accessed at: https://github.com/aldelb/non_verbal_facial_animation. CCS CONCEPTS• Computing methodologies → Neural networks; Animation.

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Section: Selected Datasetsmentioning

confidence: 99%

Towards the generation of synchronized and believable non-verbal facial behaviors of a talking virtual agent

Delbosc,

Ochs,

Sabouret

et al. 2023

International Cconference on Multimodal Interaction

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“…The cameras recorded 5-minutes rushes in .mxf format at a resolution of 1920x1080 and 25 fps. To capture clear audio, each participant was fitted with a headset microphone (AKG-C520), which was connected via XLR to the faceplate of the soundproof room and fed back to the audio-computer in the control room using a RME FireFace UC (the same sound configuration than [2,33]). The gain for each participant was adjustable using the Fireface UC and the signal was monitored in real-time using Audacity.…”

Section: Experimental Set-up and Equipmentmentioning

confidence: 99%

SMYLE: A new multimodal resource of talk-in-interaction including neuro-physiological signal

Boudin,

Bertrand,

Rauzy

et al. 2023

International Cconference on Multimodal Interaction

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This article presents the SMYLE corpus, the first multimodal corpus in French (16h) including neuro-physiological data from 60 participants engaged in face-to-face storytelling (8.2h) and free conversation tasks (7.8h). The originality of this corpus lies first in the fact that it bears all modalities, precisely synchronized and second in the addition for the first time at this scale of neuro-physiological modalities. It constitutes the first corpus of this size offering the opportunity to investigate cognitive characteristics of spontaneous conversation including at the brain level. The storytelling task comprises two conditions: a storyteller talking with a "normal" or a "distracted" listener. Contrasting normal and disrupted conversations allows to study at a behavioral, linguistic and cognitive levels the complex characteristics and organization of conversations.In this article, we present first the methodology developed to acquire and synchronize the different sources and types of signal. In a second part, we detail the large set of automatic, semi-automatic and manual annotations of the complete dataset. In a last section,

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CHEESE! : Corpus « CHEESE! »

Cited by 2 publications

References 0 publications

Towards the generation of synchronized and believable non-verbal facial behaviors of a talking virtual agent

Towards the generation of synchronized and believable non-verbal facial behaviors of a talking virtual agent

SMYLE: A new multimodal resource of talk-in-interaction including neuro-physiological signal

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