Visual scanning of a talking face when evaluating segmental and prosodic information

2020 ◽  
Vol 148 (4) ◽  
pp. 2765-2765
Author(s):  
Xizi Deng ◽  
Henny Yeung ◽  
Yue Wang
Keyword(s):  
Visual Scanning ◽  
Talking Face

Visual scanning of a talking face in preterm and full-term infants.

2019 ◽  
Vol 55 (7) ◽  
pp. 1353-1361 ◽  
Author(s):  
Elena Berdasco-Muñoz ◽  
Thierry Nazzi ◽  
H. Henny Yeung
Keyword(s):  
Full Term ◽  
Visual Scanning ◽  
Term Infants ◽  
Talking Face

Visual scanning: Comparisons between student and instructor pilots.

1976 ◽  
Author(s):  
Joseph DeMaio ◽  
Stanley Parkinson ◽  
Barry Leshowitz ◽  
John Crosby
Keyword(s):  
Visual Scanning

scholarly journals Dynamic scan paths investigations under manual and highly automated driving

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jordan Navarro ◽  
Otto Lappi ◽  
François Osiurak ◽  
Emma Hernout ◽  
Catherine Gabaude ◽  
...  
Keyword(s):  
Relative Frequency ◽  
Human Locomotion ◽  
Visual Scanning ◽  
Automated Driving ◽  
The Gaze ◽  
Visual Inputs ◽  
Gaze Patterns ◽  
Gaze Behaviour ◽  
Scan Paths ◽  
Highly Automated Driving

AbstractActive visual scanning of the scene is a key task-element in all forms of human locomotion. In the field of driving, steering (lateral control) and speed adjustments (longitudinal control) models are largely based on drivers’ visual inputs. Despite knowledge gained on gaze behaviour behind the wheel, our understanding of the sequential aspects of the gaze strategies that actively sample that input remains restricted. Here, we apply scan path analysis to investigate sequences of visual scanning in manual and highly automated simulated driving. Five stereotypical visual sequences were identified under manual driving: forward polling (i.e. far road explorations), guidance, backwards polling (i.e. near road explorations), scenery and speed monitoring scan paths. Previously undocumented backwards polling scan paths were the most frequent. Under highly automated driving backwards polling scan paths relative frequency decreased, guidance scan paths relative frequency increased, and automation supervision specific scan paths appeared. The results shed new light on the gaze patterns engaged while driving. Methodological and empirical questions for future studies are discussed.

scholarly journals Efficient End-to-End Sentence-Level Lipreading with Temporal Convolutional Networks

2021 ◽  
Vol 11 (15) ◽  
pp. 6975
Author(s):  
Tao Zhang ◽  
Lun He ◽  
Xudong Li ◽  
Guoqing Feng
Keyword(s):  
Performance Improvement ◽  
State Of The Art ◽  
Error Rates ◽  
Convolutional Network ◽  
Convolutional Networks ◽  
Sentence Level ◽  
End To End ◽  
High Level ◽  
Improved Accuracy ◽  
Talking Face

Lipreading aims to recognize sentences being spoken by a talking face. In recent years, the lipreading method has achieved a high level of accuracy on large datasets and made breakthrough progress. However, lipreading is still far from being solved, and existing methods tend to have high error rates on the wild data and have the defects of disappearing training gradient and slow convergence. To overcome these problems, we proposed an efficient end-to-end sentence-level lipreading model, using an encoder based on a 3D convolutional network, ResNet50, Temporal Convolutional Network (TCN), and a CTC objective function as the decoder. More importantly, the proposed architecture incorporates TCN as a feature learner to decode feature. It can partly eliminate the defects of RNN (LSTM, GRU) gradient disappearance and insufficient performance, and this yields notable performance improvement as well as faster convergence. Experiments show that the training and convergence speed are 50% faster than the state-of-the-art method, and improved accuracy by 2.4% on the GRID dataset.

scholarly journals Efficacy of repetitive transcranial magnetic stimulation combined with visual scanning treatment on cognitive and behavioral symptoms of left hemispatial neglect in right hemispheric stroke patients: study protocol for a randomized controlled trial

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Francesco Di Gregorio ◽  
Fabio La Porta ◽  
Emanuela Casanova ◽  
Elisabetta Magni ◽  
Roberta Bonora ◽  
...  
Keyword(s):  
Randomized Controlled Trial ◽  
Transcranial Magnetic Stimulation ◽  
Magnetic Stimulation ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Controlled Trial ◽  
Hemispatial Neglect ◽  
Visual Scanning ◽  
Stroke Patients ◽  
Rehabilitation Protocol ◽  
Randomized Controlled

Abstract Background Left hemispatial neglect (LHN) is a neuropsychological syndrome often associated with right hemispheric stroke. Patients with LHN have difficulties in attending, responding, and consciously representing the right side of space. Various rehabilitation protocols have been proposed to reduce clinical symptoms related to LHN, using cognitive treatments, or on non-invasive brain stimulation. However, evidence of their benefit is still lacking; in particular, only a few studies focused on the efficacy of combining different approaches in the same patient. Methods In the present study, we present the SMART ATLAS trial (Stimolazione MAgnetica Ripetitiva Transcranica nell’ATtenzione LAteralizzata dopo Stroke), a multicenter, randomized, controlled trial with pre-test (baseline), post-test, and 12 weeks follow-up assessments based on a novel rehabilitation protocol based on the combination of brain stimulation and standard cognitive treatment. In particular, we will compare the efficacy of inhibitory repetitive-transcranial magnetic stimulation (r-TMS), applied over the left intact parietal cortex of LHN patients, followed by visual scanning treatment, in comparison with a placebo stimulation (SHAM control) followed by the same visual scanning treatment, on visuospatial symptoms and neurophysiological parameters of LHN in a population of stroke patients. Discussion Our trial results may provide scientific evidence of a new, relatively low-cost rehabilitation protocol for the treatment of LHN. Trial registration ClinicalTrials.gov NCT04080999. Registered on September 2019.

scholarly journals Bilingualism Modulates Infants’ Selective Attention to the Mouth of a Talking Face

2015 ◽  
Vol 26 (4) ◽  
pp. 490-498 ◽  
Author(s):  
Ferran Pons ◽  
Laura Bosch ◽  
David J. Lewkowicz
Keyword(s):  
Selective Attention ◽  
Talking Face

Flightpath Tracking, Change Detection and Visual Scanning in an Integrated Hazard Display

2005 ◽  
Vol 49 (1) ◽  
pp. 68-72 ◽  
Author(s):  
Amy L. Alexander ◽  
Christopher D. Wickens
Keyword(s):  
Response Time ◽  
Change Detection ◽  
Detection Performance ◽  
Vertical Dimension ◽  
Visual Scanning ◽  
Flight Instructors ◽  
Detection Response ◽  
Step Down ◽  
Integrated Hazard ◽  
Change Detection Performance

Twenty-four certified flight instructors were required to fly a series of curved, step-down approaches while detecting changes to surrounding traffic aircraft and weather cell icons on two integrated hazard display (IHD) formats (2D coplanar and split-screen) under varying workload levels. Generally, it appears that the 2D coplanar IHD was better in supporting flightpath tracking and change detection performance when compared to a split-screen display. Pilots exhibited superior flightpath tracking (in the vertical dimension, and under low workload) when using the 2D coplanar IHD, although this effect was mitigated by increasing workload such that tracking deteriorated faster with the 2D coplanar than the split-screen display. The spawned 3D cost of diminished size with distance from ownship played a role in change detection response time—pilots were slower (particularly in detecting traffic aircraft changes) with the split-screen compared to the 2D coplanar IHD. These effects will be discussed within the context of visual scanning measures.

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