Bringing Computational Models of Word Naming Down to the Item Level

1997 ◽  
Vol 8 (6) ◽  
pp. 411-416 ◽  
Author(s):  
Daniel H. Spieler ◽  
David A. Balota
Keyword(s):  
Word Recognition ◽  
Computational Models ◽  
Predictive Power ◽  
Neighborhood Density ◽  
Word Naming ◽  
Connectionist Models ◽  
Item Level ◽  
The Individual ◽  
Level Performance ◽  
Naming Latencies

Early noncomputational models of word recognition have typically attempted to account for effects of categorical factors such as word frequency (high vs low) and spelling-to-sound regularity (regular vs irregular) More recent computational models that adhere to general connectionist principles hold the promise of being sensitive to underlying item differences that are only approximated by these categorical factors In contrast to earlier models, these connectionist models provide predictions of performance for individual items In the present study, we used the item-level estimates from two connectionist models (Plaut, McClelland, Seidenberg, & Patterson, 1996, Seidenberg & McClelland, 1989) to predict naming latencies on the individual items on which the models were trained The results indicate that the models capture, at best, slightly more variance than simple log frequency and substantially less than the combined predictive power of log frequency, neighborhood density, and orthographic length. The discussion focuses on the importance of examining the item-level performance of word-naming models and possible approaches that may improve the models' sensitivity to such item differences

scholarly journals The Predictive Power of Spatial Relational Reasoning Models: A New Evaluation Approach

2021 ◽  
Vol 12 ◽  
Author(s):  
Marco Ragni ◽  
Daniel Brand ◽  
Nicolas Riesterer
Keyword(s):  
Cognitive Modeling ◽  
Computational Models ◽  
Predictive Power ◽  
Model Comparison ◽  
Cognitive Models ◽  
Relational Reasoning ◽  
Response Patterns ◽  
Research Focus ◽  
Evaluation Approach ◽  
The Individual

In the last few decades, cognitive theories for explaining human spatial relational reasoning have increased. Few of these theories have been implemented as computational models, however, even fewer have been compared computationally to each other. A computational model comparison requires, among other things, a still missing quantitative benchmark of core spatial relational reasoning problems. By presenting a new evaluation approach, this paper addresses: (1) developing a benchmark including raw data of participants, (2) reimplementation, adaptation, and extension of existing cognitive models to predict individual responses, and (3) a thorough evaluation of the cognitive models on the benchmark data. The paper shifts the research focus of cognitive modeling from reproducing aggregated response patterns toward assessing the predictive power of models for the individual reasoner. It demonstrate that not all psychological effects can discern theories. We discuss implications for modeling spatial relational reasoning.

The Utility of Item-Level Analyses in Model Evaluation: A Reply to Seidenberg and Plaut

1998 ◽  
Vol 9 (3) ◽  
pp. 238-240 ◽  
Author(s):  
David A. Balota ◽  
Daniel H. Spieler
Keyword(s):  
Large Scale ◽  
Error Variance ◽  
Word Naming ◽  
Data Sets ◽  
Connectionist Models ◽  
Level Data ◽  
Item Level ◽  
Two Factors ◽  
Small Set ◽  
Orthographic Neighbors

Seidenberg and Plaut (this issue) argue that the implications of our analyses (Spieler & Balota, 1997) for the two extant connectionist models of word naming are limited by two factors. First, variables outside the scope of these models influence naming performance, so it is not surprising that the models do not account for much of the variance at the item level. Second, there is error variance associated with large item-level data sets that obviously should not be captured by these models. We point out that there are a number of variables that have been incorporated within the targeted connectionist models that should provide these models an advantage over the simple predictor variables that we selected as a baseline to evaluate the efficacy of the models (e.g., log frequency, length in letters, and number of orthographic neighbors). We also point out that there is considerable consistency across four large-scale studies of item means. Finally, we provide evidence that even under conditions of a standard word-naming study (with a small set of items), simple word frequency, orthographic neighborhoods, and length accounted for more variance than the extant connectionist models. We conclude that item-level analyses provide an important source of evidence in the evaluation of current models and the development of future models of visual word recognition.

Does Viotin Activate Violin More Than Viocin?

2014 ◽  
Vol 61 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Manuel Perea ◽  
Victoria Panadero
Keyword(s):  
Word Recognition ◽  
Visual Word Recognition ◽  
Developmental Dyslexia ◽  
Computational Models ◽  
Error Rates ◽  
Visual Word ◽  
Base Word ◽  
Similar Response ◽  
Skilled Readers ◽  
Young Readers

The vast majority of neural and computational models of visual-word recognition assume that lexical access is achieved via the activation of abstract letter identities. Thus, a word’s overall shape should play no role in this process. In the present lexical decision experiment, we compared word-like pseudowords like viotín (same shape as its base word: violín) vs. viocín (different shape) in mature (college-aged skilled readers), immature (normally reading children), and immature/impaired (young readers with developmental dyslexia) word-recognition systems. Results revealed similar response times (and error rates) to consistent-shape and inconsistent-shape pseudowords for both adult skilled readers and normally reading children – this is consistent with current models of visual-word recognition. In contrast, young readers with developmental dyslexia made significantly more errors to viotín-like pseudowords than to viocín-like pseudowords. Thus, unlike normally reading children, young readers with developmental dyslexia are sensitive to a word’s visual cues, presumably because of poor letter representations.

scholarly journals Effects of the Carrier Phrase on Word Recognition Performances by Younger and Older Listeners Using Two Stimulus Paradigms

2020 ◽  
Vol 31 (06) ◽  
pp. 412-441 ◽  
Author(s):  
Richard H. Wilson ◽  
Victoria A. Sanchez
Keyword(s):  
Word Recognition ◽  
Target Word ◽  
Speaker Recognition ◽  
Repeated Measures ◽  
Recognition Performance ◽  
Test Word ◽  
Root Mean Square Amplitude ◽  
Repeated Measures Design ◽  
The Mean ◽  
The Individual

Abstract Background In the 1950s, with monitored live voice testing, the vu meter time constant and the short durations and amplitude modulation characteristics of monosyllabic words necessitated the use of the carrier phrase amplitude to monitor (indirectly) the presentation level of the words. This practice continues with recorded materials. To relieve the carrier phrase of this function, first the influence that the carrier phrase has on word recognition performance needs clarification, which is the topic of this study. Purpose Recordings of Northwestern University Auditory Test No. 6 by two female speakers were used to compare word recognition performances with and without the carrier phrases when the carrier phrase and test word were (1) in the same utterance stream with the words excised digitally from the carrier (VA-1 speaker) and (2) independent of one another (VA-2 speaker). The 50-msec segment of the vowel in the target word with the largest root mean square amplitude was used to equate the target word amplitudes. Research Design A quasi-experimental, repeated measures design was used. Study Sample Twenty-four young normal-hearing adults (YNH; M = 23.5 years; pure-tone average [PTA] = 1.3-dB HL) and 48 older hearing loss listeners (OHL; M = 71.4 years; PTA = 21.8-dB HL) participated in two, one-hour sessions. Data Collection and Analyses Each listener had 16 listening conditions (2 speakers × 2 carrier phrase conditions × 4 presentation levels) with 100 randomized words, 50 different words by each speaker. Each word was presented 8 times (2 carrier phrase conditions × 4 presentation levels [YNH, 0- to 24-dB SL; OHL, 6- to 30-dB SL]). The 200 recorded words for each condition were randomized as 8, 25-word tracks. In both test sessions, one practice track was followed by 16 tracks alternated between speakers and randomized by blocks of the four conditions. Central tendency and repeated measures analyses of variance statistics were used. Results With the VA-1 speaker, the overall mean recognition performances were 6.0% (YNH) and 8.3% (OHL) significantly better with the carrier phrase than without the carrier phrase. These differences were in part attributed to the distortion of some words caused by the excision of the words from the carrier phrases. With the VA-2 speaker, recognition performances on the with and without carrier phrase conditions by both listener groups were not significantly different, except for one condition (YNH listeners at 8-dB SL). The slopes of the mean functions were steeper for the YNH listeners (3.9%/dB to 4.8%/dB) than for the OHL listeners (2.4%/dB to 3.4%/dB) and were <1%/dB steeper for the VA-1 speaker than for the VA-2 speaker. Although the mean results were clear, the variability in performance differences between the two carrier phrase conditions for the individual participants and for the individual words was striking and was considered in detail. Conclusion The current data indicate that word recognition performances with and without the carrier phrase (1) were different when the carrier phrase and target word were produced in the same utterance with poorer performances when the target words were excised from their respective carrier phrases (VA-1 speaker), and (2) were the same when the carrier phrase and target word were produced as independent utterances (VA-2 speaker).

A Critical Review of Theories and Models of Technology Adoption and Acceptance in Information System Research

2015 ◽  
Vol 6 (4) ◽  
pp. 58-77 ◽  
Author(s):  
Ali Tarhini ◽  
Nalin Asanka Gamagedara Arachchilage ◽  
Ra'ed Masa'deh ◽  
Muhammad Sharif Abbasi
Keyword(s):  
Information System ◽  
Technology Adoption ◽  
Environmental Factors ◽  
Critical Review ◽  
Predictive Power ◽  
Theoretical Models ◽  
System Research ◽  
Information System Research ◽  
Individual Level ◽  
The Individual

Previous research shows that selecting an appropriate theory or model has always remained a critical task for IS researchers. To the best of the authors' knowledge, there are few papers that review and compare the acceptance theories and models at the individual level. Hence, this article aims to overcome this problem by providing a critical review of eight of the most influential theories that have been used to predict and explain human behaviour towards adoption of various technologies at the individual level. This article also summarizes their evolution; highlight the key constructs, extensions, strengths, and criticisms from a selective list of published articles appeared in the literature related to IS. This review provides a holistic picture for future researchers in selecting appropriate single/multiple theoretical models/constructs based on their strengths and weaknesses and in terms of predictive power and path significance. It is concluded that a well-established theory should consider the personal, social, cultural, technological, organizational and environmental factors

scholarly journals A Methodology for Generation of Performance Models for the Sizing of Analog High-Level Topologies

VLSI Design ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-17
Author(s):  
Soumya Pandit ◽  
Chittaranjan Mandal ◽  
Amit Patra
Keyword(s):  
Regression Function ◽  
Support Vector ◽  
Detailed Knowledge ◽  
Performance Models ◽  
Construction Time ◽  
Level Model ◽  
The Individual ◽  
High Level ◽  
Sequence Generator ◽  
Level Performance

This paper presents a systematic methodology for the generation of high-level performance models for analog component blocks. The transistor sizes of the circuit-level implementations of the component blocks along with a set of geometry constraints applied over them define the sample space. A Halton sequence generator is used as a sampling algorithm. Performance data are generated by simulating each sampled circuit configuration through SPICE. Least squares support vector machine (LS-SVM) is used as a regression function. Optimal values of the model hyper parameters are determined through a grid search-based technique and a genetic algorithm- (GA-) based technique. The high-level models of the individual component blocks are combined analytically to construct the high-level model of a complete system. The constructed performance models have been used to implement a GA-based high-level topology sizing process. The advantages of the present methodology are that the constructed models are accurate with respect to real circuit-level simulation results, fast to evaluate, and have a good generalization ability. In addition, the model construction time is low and the construction process does not require any detailed knowledge of circuit design. The entire methodology has been demonstrated with a set of numerical results.

Connectionist models of reading

2007 ◽  
pp. 234-250 ◽  
Author(s):  
Mark S. Seidenberg
Keyword(s):  
Computational Models ◽  
Distributed Processing ◽  
Causal Effects ◽  
Task Orientation ◽  
Connectionist Models ◽  
Grain Sizes ◽  
Skilled Reading ◽  
Simple Processing ◽  
Reading Impairments ◽  
Models Of Reading

Connectionist computational models have been extensively used in the study of reading: how children learn to read, skilled reading, and reading impairments (dyslexia). The models are computer programs that simulate detailed aspects of behaviour. This article provides an overview of connectionist models of reading, with an emphasis on the “triangle” framework. The term “connectionism” refers to a broad, varied set of ideas, loosely connected by an emphasis on the notion that complexity, at different grain sizes or scales ranging from neurons to overt behaviour, emerges from the aggregate behaviour of large networks of simple processing units. This article focuses on the parallel distributed processing variety developed by Rumelhart, McClelland, and Hinton (1986). First, it describes basic elements of connectionist models of reading: task orientation, distributed representations, learning, hidden units, and experience. The article then looks at how models are used to establish causal effects, along with quasiregularity and division of labor.

Levels of Aggregation in Conjoint Analysis: An Empirical Comparison

1980 ◽  
Vol 17 (4) ◽  
pp. 516-523 ◽  
Author(s):  
William L. Moore
Keyword(s):  
Conjoint Analysis ◽  
Predictive Power ◽  
Aggregate Level ◽  
Segmentation Method ◽  
Empirical Comparison ◽  
Individual Level ◽  
Aggregate Analysis ◽  
The Individual ◽  
Level Analysis

Two segmented methods of performing conjoint anal/sis, clustered and componential segmentation, are compared with each other as well as with individual level and totally aggregate level analyses. The two segmented methods provide insights to the data that (1) are not obtainable at the aggregate level and (2) are in a form that is more easily communicated than the information from the individual level analysis. The predictive power of the clustered segmentation method is higher than that of componential segmentation, and both are superior to the aggregate analysis but inferior to individual level analysis.

Advanced Computational Analysis of Connecting Rod of an Aircraft Engine

2016 ◽  
Vol 821 ◽  
pp. 199-206 ◽  
Author(s):  
Jozef Dlugoš ◽  
Pavel Novotný ◽  
Peter Raffai
Keyword(s):  
Computational Models ◽  
Hydrodynamic Pressure ◽  
Aircraft Engine ◽  
Lubricating Oil ◽  
Connecting Rod ◽  
Temperature Dependent Viscosity ◽  
Engine Operation ◽  
The Individual ◽  
Operation Cycle ◽  
Dependent Viscosity

Development of internal combustion engine’s components is based on the use of advanced computational models in order to compare and verify the individual design proposals. Connecting rod, which performs a general planar motion, is exposed to the gas pressure forces, inertia, contacts, and hydrodynamic pressure during the engine operation cycle. To incorporate all these aspects, Finite Element Method (FEM) is extended by Finite Difference Method (FDM) simulating a slide bearing of connecting rod’s end. It includes different properties of lubricating oil (pressure and temperature dependent viscosity and density) and elastic deformations, so the pressure distribution in an oil film can be evaluated. The computational process concludes with an estimation of the endurance safety factor of the connecting rod. The four-cylinder inverted aircraft engine is used as an example.

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