scholarly journals Effects of statistical learning in passive and active contexts on reproduction and recognition of auditory sequences

2019 ◽  
Author(s):  
Saloni Krishnan ◽  
Daniel Carey ◽  
Frederic Dick ◽  
Marcus Thomas Pearce
Keyword(s):  
Statistical Learning ◽  
Recognition Performance ◽  
Transition Probability ◽  
Recognition Task ◽  
Sequence Length ◽  
Learning Mechanisms ◽  
Position Effects ◽  
Communication Signals ◽  
Sequence Recognition ◽  
Passive Exposure

Implicit statistical learning is thought to play an important role in acquiring the structure of cultural communication signals such as speech and music. These are distinguished from other sensory phenomena by the fact that we not only perceive, but also reproduce them. While research has suggested an effect of implicit learning on auditory sequence reproduction, the effect has not been specifically related to statistical learning, nor has it been compared with that of passive exposure. In eight individual experiments with different task and stimulus configurations, the present research addresses these issues by presenting artificial pure-tone languages with controlled statistical properties in passive exposure, active sequence reproduction, and explicit sequence recognition tasks. The results demonstrate that statistical learning – during either passive familiarisation or sequence reproduction – surprisingly has no effect on reproduced sequence length. However, it does induce a characteristic pattern of error position effects, newly reported here, such that errors occur more often at points of low transition probability. While sequence reproduction engages statistical learning mechanisms, there is no additive influence of passive exposure and active reproduction when the two are combined, either in terms of reproduction or recognition performance. Finally, across a large sample of participants, there is no correlation between performance on the recognition and reproduction tasks. The results are consistent with an account of statistical learning in which listeners estimate the probabilistic structure of sequential auditory stimuli during passive exposure and reproduction, and then subsequently extract and memorise chunks based on this information when asked to do so in an explicit recognition task.

scholarly journals Recognising the dynamic form of fire

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fintan Nagle ◽  
Alan Johnston
Keyword(s):  
Sequential Analysis ◽  
Recognition Performance ◽  
Human Vision ◽  
Sequence Length ◽  
False Alarms ◽  
Analysis Model ◽  
Sequence Recognition ◽  
Asymmetric Pattern ◽  
Dynamic Form ◽  
Decision Making Model

AbstractEncoding and recognising complex natural sequences provides a challenge for human vision. We found that observers could recognise a previously presented segment of a video of a hearth fire when embedded in a longer sequence. Recognition performance declined when the test video was spatially inverted, but not when it was hue reversed or temporally reversed. Sampled motion degraded forwards/reversed playback discrimination, indicating observers were sensitive to the asymmetric pattern of motion of flames. For brief targets, performance increased with target length. More generally, performance depended on the relative lengths of the target and embedding sequence. Increased errors with embedded sequence length were driven by positive responses to non-target sequences (false alarms) rather than omissions. Taken together these observations favour interpreting performance in terms of an incremental decision-making model based on a sequential statistical analysis in which evidence accrues for one of two alternatives. We also suggest that prediction could provide a means of providing and evaluating evidence in a sequential analysis model.

scholarly journals Semi-Supervised Joint Learning for Hand Gesture Recognition from a Single Color Image

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 1007
Author(s):  
Chi Xu ◽  
Yunkai Jiang ◽  
Jun Zhou ◽  
Yi Liu
Keyword(s):  
Gesture Recognition ◽  
Pose Estimation ◽  
Color Image ◽  
Recognition Performance ◽  
Recognition Task ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Estimation Task ◽  
Hand Pose Estimation ◽  
Hand Pose

Hand gesture recognition and hand pose estimation are two closely correlated tasks. In this paper, we propose a deep-learning based approach which jointly learns an intermediate level shared feature for these two tasks, so that the hand gesture recognition task can be benefited from the hand pose estimation task. In the training process, a semi-supervised training scheme is designed to solve the problem of lacking proper annotation. Our approach detects the foreground hand, recognizes the hand gesture, and estimates the corresponding 3D hand pose simultaneously. To evaluate the hand gesture recognition performance of the state-of-the-arts, we propose a challenging hand gesture recognition dataset collected in unconstrained environments. Experimental results show that, the gesture recognition accuracy of ours is significantly boosted by leveraging the knowledge learned from the hand pose estimation task.

Investigating implicit statistical learning mechanisms through contextual cueing

2015 ◽  
Vol 19 (9) ◽  
pp. 524-533 ◽  
Author(s):  
Annabelle Goujon ◽  
André Didierjean ◽  
Simon Thorpe
Keyword(s):  
Statistical Learning ◽  
Contextual Cueing ◽  
Learning Mechanisms

Classroom Noise and Children Learning Through a Second Language

2005 ◽  
Vol 36 (3) ◽  
pp. 219-229 ◽  
Author(s):  
Peggy Nelson ◽  
Kathryn Kohnert ◽  
Sabina Sabur ◽  
Daniel Shaw
Keyword(s):  
Second Language ◽  
Word Recognition ◽  
Signal To Noise Ratio ◽  
Recognition Performance ◽  
Recognition Task ◽  
English Word ◽  
Noise Condition ◽  
English Only ◽  
Task Behavior ◽  
The Impact

Purpose: Two studies were conducted to investigate the effects of classroom noise on attention and speech perception in native Spanish-speaking second graders learning English as their second language (L2) as compared to English-only-speaking (EO) peers. Method: Study 1 measured children’s on-task behavior during instructional activities with and without soundfield amplification. Study 2 measured the effects of noise (+10 dB signal-to-noise ratio) using an experimental English word recognition task. Results: Findings from Study 1 revealed no significant condition (pre/postamplification) or group differences in observations in on-task performance. Main findings from Study 2 were that word recognition performance declined significantly for both L2 and EO groups in the noise condition; however, the impact was disproportionately greater for the L2 group. Clinical Implications: Children learning in their L2 appear to be at a distinct disadvantage when listening in rooms with typical noise and reverberation. Speech-language pathologists and audiologists should collaborate to inform teachers, help reduce classroom noise, increase signal levels, and improve access to spoken language for L2 learners.

scholarly journals Data Augmentation-Assisted Makeup-Invariant Face Recognition

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Muhammad Sajid ◽  
Nouman Ali ◽  
Saadat Hanif Dar ◽  
Naeem Iqbal Ratyal ◽  
Asif Raza Butt ◽  
...  
Keyword(s):  
Face Recognition ◽  
Data Augmentation ◽  
Recognition Performance ◽  
Recognition Task ◽  
Face Images ◽  
Face Features ◽  
Face Datasets ◽  
Exponential Rates ◽  
Interpersonal Situations

Recently, face datasets containing celebrities photos with facial makeup are growing at exponential rates, making their recognition very challenging. Existing face recognition methods rely on feature extraction and reference reranking to improve the performance. However face images with facial makeup carry inherent ambiguity due to artificial colors, shading, contouring, and varying skin tones, making recognition task more difficult. The problem becomes more confound as the makeup alters the bilateral size and symmetry of the certain face components such as eyes and lips affecting the distinctiveness of faces. The ambiguity becomes even worse when different days bring different facial makeup for celebrities owing to the context of interpersonal situations and current societal makeup trends. To cope with these artificial effects, we propose to use a deep convolutional neural network (dCNN) using augmented face dataset to extract discriminative features from face images containing synthetic makeup variations. The augmented dataset containing original face images and those with synthetic make up variations allows dCNN to learn face features in a variety of facial makeup. We also evaluate the role of partial and full makeup in face images to improve the recognition performance. The experimental results on two challenging face datasets show that the proposed approach can compete with the state of the art.

scholarly journals Is Pupil Activity Associated With the Strength of Memory Signal for Words in a Continuous Recognition Memory Paradigm?

2021 ◽  
Vol 12 ◽  
Author(s):  
Jorge Oliveira ◽  
Marta Fernandes ◽  
Pedro J. Rosa ◽  
Pedro Gamito
Keyword(s):  
Retention Interval ◽  
Recognition Memory ◽  
Pupil Size ◽  
Time Course ◽  
Recognition Performance ◽  
Recognition Task ◽  
Subjective Feeling ◽  
Consistent Finding ◽  
Pupillary Responses ◽  
Study Test

Research on pupillometry provides an increasing evidence for associations between pupil activity and memory processing. The most consistent finding is related to an increase in pupil size for old items compared with novel items, suggesting that pupil activity is associated with the strength of memory signal. However, the time course of these changes is not completely known, specifically, when items are presented in a running recognition task maximizing interference by requiring the recognition of the most recent items from a sequence of old/new items. The sample comprised 42 healthy participants who performed a visual word recognition task under varying conditions of retention interval. Recognition responses were evaluated using behavioral variables for discrimination accuracy, reaction time, and confidence in recognition decisions. Pupil activity was recorded continuously during the entire experiment. The results suggest a decrease in recognition performance with increasing study-test retention interval. Pupil size decreased across retention intervals, while pupil old/new effects were found only for words recognized at the shortest retention interval. Pupillary responses consisted of a pronounced early pupil constriction at retrieval under longer study-test lags corresponding to weaker memory signals. However, the pupil size was also sensitive to the subjective feeling of familiarity as shown by pupil dilation to false alarms (new items judged as old). These results suggest that the pupil size is related not only to the strength of memory signal but also to subjective familiarity decisions in a continuous recognition memory paradigm.

scholarly journals The effect of repetition priming on implicit recognition memory as measured by Fast Periodic Visual Stimulation and EEG

2020 ◽  
Author(s):  
Volkan Nurdal ◽  
Graeme Fairchild ◽  
George Stothart
Keyword(s):  
Recognition Memory ◽  
Repetition Priming ◽  
Visual Memory ◽  
Assessment Tool ◽  
Visual Stimulation ◽  
Recognition Performance ◽  
Recognition Task ◽  
Oddball Paradigm ◽  
Repetition Condition ◽  
Memory Response

Introduction: The development of rapid and reliable neural measures of memory is an important goal of cognitive neuroscience research and clinical practice. Fast Periodic Visual Stimulation (FPVS) is a recently developed electroencephalography (EEG) method that involves presenting a mix of novel and previously-learnt stimuli at a fast rate. Recent work has shown that implicit recognition memory can be measured using FPVS, however the role of repetition priming remains unclear. Here, we attempted to separate out the effects of recognition memory and repetition priming by manipulating the degree of repetition of the stimuli to be remembered.Method: Twenty-two participants with a mean age of 20.8 (±4.3) yrs completed an FPVS-oddball paradigm with a varying number of repetitions of the oddball stimuli, ranging from repetition only (pure repetition) to no repetition (pure recognition). In addition to the EEG task, participants completed a behavioural recognition task and visual memory subtests from the Wechsler Memory Scale – 4th edition (WMS-IV). Results: An oddball memory response was observed in all four experimental conditions (pure repetition to pure recognition) compared to the control condition (no oddball stimuli). The oddball memory response was largest in the pure repetition condition and smaller, but still significant, in conditions with less/no oddball repetition (e.g. pure recognition). Behavioural recognition performance was at ceiling, suggesting that all images were encoded successfully. There was no correlation with either behavioural memory performance or WMS-IV scores, suggesting the FPVS-oddball paradigm captures different memory processes than behavioural measures.Conclusion: Repetition priming significantly modulates the FPVS recognition memory response, however recognition is still detectable even in the total absence of repetition priming. The FPVS-oddball paradigm could potentially be developed into an objective and easy-to-administer memory assessment tool.

DMMs-Based Multiple Features Fusion for Human Action Recognition

2015 ◽  
Vol 6 (4) ◽  
pp. 23-39 ◽  
Author(s):  
Mohammad Farhad Bulbul ◽  
Yunsheng Jiang ◽  
Jinwen Ma
Keyword(s):  
Action Recognition ◽  
Recognition Performance ◽  
Recognition Task ◽  
Human Action Recognition ◽  
Fusion Rule ◽  
Local Binary Patterns ◽  
Human Action ◽  
Decision Fusion ◽  
Soft Decision ◽  
Depth Sensors

The emerging cost-effective depth sensors have facilitated the action recognition task significantly. In this paper, the authors address the action recognition problem using depth video sequences combining three discriminative features. More specifically, the authors generate three Depth Motion Maps (DMMs) over the entire video sequence corresponding to the front, side, and top projection views. Contourlet-based Histogram of Oriented Gradients (CT-HOG), Local Binary Patterns (LBP), and Edge Oriented Histograms (EOH) are then computed from the DMMs. To merge these features, the authors consider decision-level fusion, where a soft decision-fusion rule, Logarithmic Opinion Pool (LOGP), is used to combine the classification outcomes from multiple classifiers each with an individual set of features. Experimental results on two datasets reveal that the fusion scheme achieves superior action recognition performance over the situations when using each feature individually.

Relational problems are not fully solved by a temporal sequence of statistical learning episodes

1997 ◽  
Vol 20 (1) ◽  
pp. 82-82 ◽  
Author(s):  
A. Vinter ◽  
P. Perruchet
Keyword(s):  
Implicit Learning ◽  
Statistical Learning ◽  
Temporal Sequence ◽  
The Other ◽  
Learning Mechanisms ◽  
Learning Research ◽  
The One

Clark & Thornton's conception finds an echo in implicit learning research, which shows that subjects may perform adaptively in complex structured situations through the use of simple statistical learning mechanisms. However, the authors fail to draw a distinction between, on the one hand, subjects' representations which emerge from type-1 learning mechanisms, and, on the other, their knowledge of the genuine abstract “recoding function” which defines a type-2 problem.

scholarly journals The role of divided attention and expertise in melody recognition

2017 ◽  
Vol 23 (1) ◽  
pp. 69-86 ◽  
Author(s):  
Steffen A. Herff ◽  
Daniela Czernochowski
Keyword(s):  
Divided Attention ◽  
Recognition Performance ◽  
Recognition Task ◽  
Attentional Resource ◽  
Attention And Memory ◽  
Attention Condition ◽  
Monitoring Task ◽  
Melody Recognition ◽  
Musical Expertise

When attention is divided during memory encoding, performance tends to suffer. The nature of this performance decrement, however, is domain-dependent and often governed by domain-specific expertise. In this study, 111 participants with differing levels of musical expertise (professional musicians, amateur musicians, and non-musicians) were presented with novel melodies under full- or divided-attention conditions in a continuous melody-recognition task. As hypothesized, melody recognition was modulated by musical expertise, as greater expertise was associated with better performance. Recognition performance increased with every additional presentation of a target melody. The divided-attention condition required concurrently performing a non-music related digit-monitoring task while simultaneously listening to the melodies. Memory performance decreased universally in all groups in the divided-attention condition; however, intriguingly musicians also performed significantly better in the concurrent digit-monitoring task than non-musicians. Results provide insight into the role of expertise, attention, and memory in the musical domain, and are discussed in terms of attentional resource models. In light of resource models, an asymmetrical non-linear trade-off between two simultaneous tasks is proposed to explain the present findings.

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