scholarly journals Can computers understand words like humans do? Comparable semantic representation in neural and computer systems

2019 ◽  
Author(s):  
Linmin Zhang ◽  
Lingting Wang ◽  
Jinbiao Yang ◽  
Peng Qian ◽  
Xuefei Wang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Word Processing ◽  
Semantic Processing ◽  
Computational Models ◽  
Time Window ◽  
Early Stage ◽  
Semantic Representation ◽  
Deep Understanding ◽  
Joint Force ◽  
Strong Artificial Intelligence

AbstractSemantic representation has been studied independently in neuroscience and computer science. A deep understanding of human neural computations and the revolution to strong artificial intelligence appeal for a joint force in the language domain. We investigated comparable representational formats of lexical semantics between these two complex systems with fine temporal resolution neural recordings. We found semantic representations generated from computational models significantly correlated with EEG responses at an early stage of a typical semantic processing time window in a two-word semantic priming paradigm. Moreover, three representative computational models differentially predicted EEG responses along the dynamics of word processing. Our study provided a finer-grained understanding of the neural dynamics underlying semantic processing and developed an objective biomarker for assessing human-like computation in computational models. Our novel framework trailblazed a promising way to bridge across disciplines in the investigation of higher-order cognitive functions in human and artificial intelligence.

scholarly journals Parallel Processing of Semantics and Phonology in Spoken Production: Evidence from Blocked Cyclic Picture Naming and EEG

2021 ◽  
pp. 1-14 ◽  
Author(s):  
Chen Feng ◽  
Markus F. Damian ◽  
Qingqing Qu
Keyword(s):  
Cognitive Processes ◽  
Language Production ◽  
Semantic Processing ◽  
Time Course ◽  
Time Window ◽  
Early Stage ◽  
Phonological Information ◽  
Relative Time ◽  
Similar Time ◽  
Semantic Access

Spoken language production involves lexical-semantic access and phonological encoding. A theoretically important question concerns the relative time course of these two cognitive processes. The predominant view has been that semantic and phonological codes are accessed in successive stages. However, recent evidence seems difficult to reconcile with a sequential view but rather suggests that both types of codes are accessed in parallel. Here, we used ERPs combined with the “blocked cyclic naming paradigm” in which items overlapped either semantically or phonologically. Behaviorally, both semantic and phonological overlap caused interference relative to unrelated baseline conditions. Crucially, ERP data demonstrated that the semantic and phonological effects emerged at a similar latency (∼180 msec after picture onset) and within a similar time window (180–380 msec). These findings suggest that access to phonological information takes place at a relatively early stage during spoken planning, largely in parallel with semantic processing.

The Role of Theories of Embodied Cognition in Research and Modeling of Emotions

2019 ◽  
Vol 62 (5) ◽  
pp. 124-138
Author(s):  
Alexandra V. Shiller
Keyword(s):  
Artificial Intelligence ◽  
Embodied Cognition ◽  
Mirror Neurons ◽  
Empirical Studies ◽  
Unknown Quantity ◽  
Emotional Processes ◽  
Strong Artificial Intelligence ◽  
European Philosophy ◽  
Postmodern Philosophy

The article analyzes the role of theories of embodied cognition for the development of emotion research. The role and position of emotions changed as philosophy developed. In classical and modern European philosophy, the idea of the “primacy of reason” prevailed over emotions and physicality, emotions and affective life were described as low-ranking phenomena regarding cognitive processes or were completely eliminated as an unknown quantity. In postmodern philosophy, attention focuses on physicality and sensuality, which are rated higher than rational principle, mind and intelligence. Within the framework of this approach, there is a recently emerged theory of embodied cognition, which allows to take a fresh look at the place of emotions in the architecture of mental processes – thinking, perception, memory, imagination, speech. The article describes and analyzes a number of empirical studies showing the impossibility of excluding emotional processes and the significance of their research for understanding the architecture of embodied cognition. However, the features of the architecture of embodied cognition remain unclear, and some of the discoveries of recent years (mirror neurons or neurons of simulation) rather raise new questions and require further research. The rigorously described and clear architecture of the embodied cognition can grow the theoretical basis that will allow to advance the studies of learning processes, language understanding, psychotherapy techniques, social attitudes and stereotypes, highlight the riddle of consciousness and create new theories of consciousness or even create an anthropomorphic artificial intelligence that is close to “strong artificial intelligence.”

The Opposition of Surprisal and Semantic Similarity in the Prediction of Language Processing: Evidence from Eye-tracking Data

2020 ◽  
Author(s):  
Kun Sun
Keyword(s):  
Eye Tracking ◽  
Semantic Similarity ◽  
Cognitive Processing ◽  
Language Processing ◽  
Language Comprehension ◽  
Word Processing ◽  
Reading Time ◽  
Computational Models ◽  
Tracking Data ◽  
Dynamic Approach

Expectations or predictions about upcoming content play an important role during language comprehension and processing. One important aspect of recent studies of language comprehension and processing concerns the estimation of the upcoming words in a sentence or discourse. Many studies have used eye-tracking data to explore computational and cognitive models for contextual word predictions and word processing. Eye-tracking data has previously been widely explored with a view to investigating the factors that influence word prediction. However, these studies are problematic on several levels, including the stimuli, corpora, statistical tools they applied. Although various computational models have been proposed for simulating contextual word predictions, past studies usually preferred to use a single computational model. The disadvantage of this is that it often cannot give an adequate account of cognitive processing in language comprehension. To avoid these problems, this study draws upon a massive natural and coherent discourse as stimuli in collecting the data on reading time. This study trains two state-of-art computational models (surprisal and semantic (dis)similarity from word vectors by linear discriminative learning (LDL)), measuring knowledge of both the syntagmatic and paradigmatic structure of language. We develop a `dynamic approach' to compute semantic (dis)similarity. It is the first time that these two computational models have been merged. Models are evaluated using advanced statistical methods. Meanwhile, in order to test the efficiency of our approach, one recently developed cosine method of computing semantic (dis)similarity based on word vectors data adopted is used to compare with our `dynamic' approach. The two computational and fixed-effect statistical models can be used to cross-verify the findings, thus ensuring that the result is reliable. All results support that surprisal and semantic similarity are opposed in the prediction of the reading time of words although both can make good predictions. Additionally, our `dynamic' approach performs better than the popular cosine method. The findings of this study are therefore of significance with regard to acquiring a better understanding how humans process words in a real-world context and how they make predictions in language cognition and processing.

‘Higher then to her no bookes doe reach’

2018 ◽  
Author(s):  
Martha Vandrei
Keyword(s):  
Early Stage ◽  
Deep Understanding ◽  
Contemporary Philosophy ◽  
James I ◽  
Historical Method ◽  
The Past ◽  
Classical World ◽  
Material Evidence ◽  
Do So

This chapter and the following both draw the reader into seventeenth-century understandings of the past, and of Boudica in particular, and makes clear that in a time before disciplines, writers of ‘history’ were erudite commentators, immersed in political thought, the classical world, and contemporary ideas, as well as in drama, poetry, and the law. Chapter 1 shows the subtleties of Boudica’s place in history at this early stage by giving sustained attention to the work of Edmund Bolton (1574/5–c.1634), the first person to analyse the written and material evidence for Boudica’s deeds, and the last to do so in depth before the later nineteenth century. Bolton’s distaste for contemporary philosophy and his loyalty to James I were highly influential in determining the way the antiquary approached Boudica and her rebellion; but equally important was Bolton’s deep understanding of historical method and the strictures this placed on his interpretive latitude.

Computing Possible Futures

2019 ◽  
Author(s):  
William B. Rouse
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computational Modeling ◽  
Mental Model ◽  
Data Analytics ◽  
Computational Models ◽  
Senior Managers ◽  
Interactive Visualizations ◽  
Use Of Models ◽  
Better Than

This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what “data analytics” can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are reasonably skeptical, having experienced overselling and under-delivery. They ask about reasonable and realistic expectations. Their concern is with the futurity of decisions they are currently entertaining. They cannot fully address this concern empirically. Thus, they need some way to make predictions. The problem is that one rarely can predict exactly what will happen, only what might happen. To overcome this limitation, executives can be provided predictions of possible futures and the conditions under which each scenario is likely to emerge. Models can help them to understand these possible futures. Most executives find such candor refreshing, perhaps even liberating. Their job becomes one of imagining and designing a portfolio of possible futures, assisted by interactive computational models. Understanding and managing uncertainty is central to their job. Indeed, doing this better than competitors is a hallmark of success. This book is intended to help them understand what fundamentally needs to be done, why it needs to be done, and how to do it. The hope is that readers will discuss this book and develop a “shared mental model” of computational modeling in the process, which will greatly enhance their chances of success.

scholarly journals Out of the loop? On the radical and the routine in urban big data

Urban Studies ◽  
2021 ◽  
pp. 004209802110140
Author(s):  
Sarah Barns
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Computational Models ◽  
Data Driven ◽  
Urban Systems ◽  
Out Of The Loop ◽  
Urban Futures ◽  
Urban Behaviour ◽  
The City

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.

Semantic processing in connected speech at a uniformly early stage of autopsy-confirmed Alzheimer's disease.

2013 ◽  
Vol 27 (1) ◽  
pp. 79-85 ◽  
Author(s):  
Samrah Ahmed ◽  
Celeste A. de Jager ◽  
Anne-Marie Haigh ◽  
Peter Garrard
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Semantic Processing ◽  
Early Stage ◽  
Connected Speech

scholarly journals Effect of the Intra-Abdominal Pressure and the Center of Segmental Body Mass on the Lumbar Spine Mechanics – A Computational Parametric Study

2012 ◽  
Vol 134 (1) ◽  
Author(s):  
W. M. Park ◽  
S. Wang ◽  
Y. H. Kim ◽  
K. B. Wood ◽  
J. A. Sim ◽  
...  
Keyword(s):  
Lumbar Spine ◽  
Computational Models ◽  
Muscle Force ◽  
Weight Bearing ◽  
Upper Body ◽  
Abdominal Pressure ◽  
Lumbosacral Spine ◽  
Simulation Accuracy ◽  
Joint Force ◽  
Geometric Center

Determination of physiological loads in human lumbar spine is critical for understanding the mechanisms of lumbar diseases and for designing surgical treatments. Computational models have been used widely to estimate the physiological loads of the spine during simulated functional activities. However, various assumptions on physiological factors such as the intra-abdominal pressure (IAP), centers of mass (COMs) of the upper body and lumbar segments, and vertebral centers of rotation (CORs) have been made in modeling techniques. Systematic knowledge of how these assumptions will affect the predicted spinal biomechanics is important for improving the simulation accuracy. In this paper, we developed a 3D subject-specific numerical model of the lumbosacral spine including T12 and 90 muscles. The effects of the IAP magnitude and COMs locations on the COR of each motion segment and on the joint/muscle forces were investigated using a global convergence optimization procedure when the subject was in a weight bearing standing position. The data indicated that the line connecting the CORs showed a smaller curvature than the lordosis of the lumbar spine in standing posture when the IAP was 0 kPa and the COMs were 10 mm anterior to the geometric center of the T12 vertebra. Increasing the IAP from 0 kPa to 10 kPa shifted the location of CORs toward the posterior direction (from 1.4 ± 8.9 mm anterior to intervertebral disc (IVD) centers to 40.5 ± 3.1 mm posterior to the IVD centers) and reduced the average joint force (from 0.78 ± 0.11 Body weight (BW) to 0.31 ± 0.07 BW) and overall muscle force (from 349.3 ± 57.7 N to 221.5 ± 84.2 N). Anterior movement of the COMs from −30 mm to 70 mm relative to the geometric center of T12 vertebra caused an anterior shift of the CORs (from 25.1 ± 8.3 mm posterior to IVD centers to 7.8 ± 6.2 mm anterior to IVD centers) and increases of average joint forces (from 0.78 ± 0.1 BW to 0.93 ± 0.1 BW) and muscle force (from 348.9 ± 47.7 N to 452.9 ± 58.6 N). Therefore, it is important to consider the IAP and correct COMs in order to accurately simulate human spine biomechanics. The method and results of this study could be useful for designing prevention strategies of spinal injuries and recurrences, and for enhancing rehabilitation efficiency.

scholarly journals N170 reflects visual familiarity and automatic sublexical phonological access in L2 written word processing

2021 ◽  
pp. 1-11
Author(s):  
Yen Na Yum ◽  
Sam-Po Law
Keyword(s):  
Phonological Processing ◽  
Word Processing ◽  
Time Window ◽  
Mixed Effects Models ◽  
Linear Mixed Effects Models ◽  
Linear Mixed Effects ◽  
Repetition Detection ◽  
Korean Chinese ◽  
Written Word ◽  
Bilingual Readers

Abstract The literature has mixed reports on whether the N170, an early visual ERP response to words, signifies orthographic and/or phonological processing, and whether these effects are moderated by script and language expertise. In this study, native Chinese readers, Japanese–Chinese, and Korean–Chinese bilingual readers performed a one-back repetition detection task with single Chinese characters that differed in phonological regularity status. Results using linear mixed effects models showed that Korean–Chinese readers had bilateral N170 response, while native Chinese and Japanese–Chinese groups had left-lateralized N170, with stronger left lateralization in native Chinese than Japanese–Chinese readers. Additionally, across groups, irregular characters had bilateral increase in N170 amplitudes compared to regular characters. These results suggested that visual familiarity to a script rather than orthography-phonology mapping determined the left lateralization of the N170 response, while there was automatic access to sublexical phonology in the N170 time window in native and non-native readers alike.

Lexical and sentential priming in competition: Implications for two-stage theories of lexical access

2001 ◽  
Vol 22 (2) ◽  
pp. 191-215 ◽  
Author(s):  
ARTURO E. HERNANDEZ ◽  
CHRISTINE FENNEMA-NOTESTINE ◽  
CARE UDELL ◽  
ELIZABETH BATES
Keyword(s):  
Lexical Access ◽  
Time Window ◽  
Early Stage ◽  
Time Windows ◽  
Unrelated Word ◽  
Two Stage ◽  
Sentential Context ◽  
Lexical Priming ◽  
Priming Word ◽  
Stage Theories

This article presents a new method that can compare lexical priming (word–word) and sentential priming (sentence–word) directly within a single paradigm. We show that it can be used to address modular theories of word comprehension, which propose that the effects of sentence context occur after lexical access has taken place. Although lexical priming and sentential priming each occur very quickly in time, there should be a brief time window in which the former is present but the latter is absent. Lexical and sentential priming of unambiguous words were evaluated together, in competing and converging combinations, using time windows designed to detect an early stage where lexical priming is observed but sentential priming is not. Related and unrelated word pairs were presented visually, in rapid succession, within auditory sentence contexts that were either compatible or incompatible with the target (the second word in each pair). In lexical decision, the additive effects of lexical priming and sentential priming were present under all temporal conditions, although the latter was always substantially larger. In cross-modal naming, sentential priming was present in all temporal conditions; lexical priming was more fragile, interacting with timing and sentential congruence. No evidence was found for a stage in which lexical priming is present but sentential priming is absent – a finding that is difficult to reconcile with two-stage models of lexical versus sentential priming. We conclude that sentential context operates very early in the process of word recognition, and that it can interact with lexical priming at the earliest time window.

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