2 |
Paraverbal Expression of Verbal Irony: Vocal Cues Matter and Facial Cues Even More
|
|
|
|
In: ISSN: 0191-5886 ; EISSN: 1573-3653 ; Journal of Nonverbal Behavior ; https://hal.archives-ouvertes.fr/hal-03377915 ; Journal of Nonverbal Behavior, Springer Verlag, 2021, ⟨10.1007/s10919-021-00385-z⟩ (2021)
|
|
BASE
|
|
Show details
|
|
3 |
A Cross-cultural Study of Serbian and English Native Speakers’ Non-verbal Actions and Identity During a Videoconferencing Task in New Zealand
|
|
|
|
BASE
|
|
Show details
|
|
4 |
Integration of Social Context vs. Linguistic Reference During Situated Language Processing ...
|
|
|
|
BASE
|
|
Show details
|
|
5 |
THE IMPORTANCE OF NON-VERBAL COMMUNICATIONIN TEACHING AND LEARNINGA FOREIGN LANGUAGE ...
|
|
|
|
BASE
|
|
Show details
|
|
6 |
THE IMPORTANCE OF NON-VERBAL COMMUNICATIONIN TEACHING AND LEARNINGA FOREIGN LANGUAGE ...
|
|
|
|
BASE
|
|
Show details
|
|
7 |
The impact of facial expressions in consumer purchase decision
|
|
|
|
BASE
|
|
Show details
|
|
8 |
Integration of Social Context vs. Linguistic Reference During Situated Language Processing
|
|
|
|
BASE
|
|
Show details
|
|
10 |
Multimodal practices for negative assessments as delicate matters: Incomplete syntax, facial expressions, and head movements
|
|
|
|
In: Open Linguistics, Vol 7, Iss 1, Pp 549-568 (2021) (2021)
|
|
BASE
|
|
Show details
|
|
11 |
Some consideration on expressive audiovisual speech corpus acquisition using a multimodal platform
|
|
|
|
In: ISSN: 1574-020X ; EISSN: 1574-0218 ; Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-02907046 ; Language Resources and Evaluation, Springer Verlag, 2020, ⟨10.1007/s10579-020-09500-w⟩ ; https://link.springer.com/article/10.1007%2Fs10579-020-09500-w (2020)
|
|
Abstract:
International audience ; In this paper, we present a multimodal acquisition setup that combines different motion-capture systems. This system is mainly aimed for recording expressive audiovisual corpus in the context of audiovisual speech synthesis. When dealing with speech recording, the standard optical motion-capture systems fail in tracking the articulators finely, especially the inner mouth region, due to the disappearing of certain markers during the articulation. Also, some systems have limited frame rates and are not suitable for smooth speech tracking. In this work, we demonstrate how those limitations can be overcome by creating a heterogeneous system taking advantage of different tracking systems. In the scope of this work, we recorded a prototypical corpus using our combined system for a single subject. This corpus was used to validate our multimodal data acquisition protocol and to assess the quality of the expressiveness before recording a large corpus. We conducted two evaluations of the recorded data, the first one concerns the production aspect of speech and the second one focuses on the speech perception aspect (both evaluations concern visual and acoustic modalities). Production analysis allowed us to identify characteristics specific to each expressive context. This analysis showed that the expressive content of the recorded data is globally in line with what is commonly expected in the literature. The perceptual evaluation, conducted as a human emotion recognition task using different types of stimulus, confirmed that the different recorded emotions were well perceived.
|
|
Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]; [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]; [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing; Acted speech; Expressive audiovisual speech; Facial expressions
|
|
URL: https://doi.org/10.1007/s10579-020-09500-w https://hal.archives-ouvertes.fr/hal-02907046/document https://hal.archives-ouvertes.fr/hal-02907046/file/LREV-4.pdf https://hal.archives-ouvertes.fr/hal-02907046
|
|
BASE
|
|
Hide details
|
|
12 |
A Comparison of the Affectiva iMotions Facial Expression Analysis Software With EMG for Identifying Facial Expressions of Emotion
|
|
|
|
BASE
|
|
Show details
|
|
13 |
Providing Students with Multimodal Feedback Experiences
|
|
|
|
In: Journal of Curriculum, Teaching, Learning and Leadership in Education (2020)
|
|
BASE
|
|
Show details
|
|
14 |
Visual Behavior, Pupil Dilation, and Ability to Identify Emotions From Facial Expressions After Stroke
|
|
|
|
BASE
|
|
Show details
|
|
15 |
Annotation and data-driven synthesis of facial expressions of French sign language ; Annotation et synthèse basée données des expressions faciales de la Langue des Signes Française
|
|
|
|
In: https://hal.archives-ouvertes.fr/tel-03080311 ; Computer science. Université Bretagne-Sud, 2019. English (2019)
|
|
BASE
|
|
Show details
|
|
16 |
System for Face Recognition under Different Facial Expressions Using a New Associative Hybrid Model Amαβ-KNN for People with Visual Impairment or Prosopagnosia
|
|
|
|
In: Sensors ; Volume 19 ; Issue 3 (2019)
|
|
BASE
|
|
Show details
|
|
17 |
Aspie Quiz: projeto de aplicação móvel de apoio à identificação de emoções, para portadores de Síndrome de Asperger
|
|
|
|
BASE
|
|
Show details
|
|
18 |
Predicting free-riding in a public goods game: Analysis of content and dynamic facial expressions in face-to-face communication
|
|
|
|
BASE
|
|
Show details
|
|
19 |
Impact of the face registration techniques on facial expressions recognition
|
|
|
|
In: ISSN: 0923-5965 ; EISSN: 1879-2677 ; Signal Processing: Image Communication ; https://hal.archives-ouvertes.fr/hal-01644769 ; Signal Processing: Image Communication, Elsevier, 2018, 61, pp.44-53. ⟨10.1016/j.image.2017.11.002⟩ (2018)
|
|
BASE
|
|
Show details
|
|
20 |
A study of facial expression recognition technologies on deaf adults and their children
|
|
|
|
BASE
|
|
Show details
|
|
|
|