The Novel Object and Unusual Name (NOUN) Database: A collection of novel images for use in experimental research

Many experimental research designs require images of novel objects. Here we introduce the Novel Object and Unusual Name (NOUN) Database. This database contains 64 primary novel object images and additional novel exemplars for ten basic- and nine global-level object categories. The objects’ novelty was confirmed by both self-report and a lack of consensus on questions that required participants to name and identify the objects. We also found that object novelty correlated with qualifying naming responses pertaining to the objects’ colors. The results from a similarity sorting task (and a subsequent multidimensional scaling analysis on the similarity ratings) demonstrated that the objects are complex and distinct entities that vary along several featural dimensions beyond simply shape and color. A final experiment confirmed that additional item exemplars comprised both sub- and superordinate categories. These images may be useful in a variety of settings, particularly for developmental psychology and other research in the language, categorization, perception, visual memory, and related domains.

[1]  A. Fernald,et al.  Fast mapping, slow learning: Disambiguation of novel word–object mappings in relation to vocabulary learning at 18, 24, and 30months , 2013, Cognition.

[2]  P. Luce,et al.  When Words Compete: Levels of Processing in Perception of Spoken Words , 1998 .

[3]  Alexander K. Smith,et al.  Conducting High-Value Secondary Dataset Analysis: An Introductory Guide and Resources , 2011, Journal of General Internal Medicine.

[4]  Ellen M. Migo,et al.  A visual object stimulus database with standardized similarity information , 2013, Behavior research methods.

[5]  Linda B. Smith,et al.  Object Shape, Object Function, and Object Name , 1998 .

[6]  Stephen D. Goldinger,et al.  Learning in repeated visual search , 2010, Attention, perception & psychophysics.

[7]  Jeremy M Wolfe,et al.  Journal of Experimental Psychology : General The Role of Object Categories in Hybrid Visual and Memory Search , 2014 .

[8]  M. Casasola,et al.  Acquisition of word-object associations by 14-month-old infants. , 1998 .

[9]  R. Nosofsky.  Attention, similarity, and the identification-categorization relationship. , 1986, Journal of experimental psychology. General.

[10]  A. Springall,et al.  A review of multidimensional scaling , 1978 .

[11]  J. V. van Berkum,et al.  How robust is the language architecture? The case of mood , 2013, Front. Psychol..

[12]  Linda B. Smith,et al.  Early noun vocabularies: do ontology, category structure and syntax correspond? , 1999, Cognition.

[13]  Linda B Smith,et al.  They call it like they see it: spontaneous naming and attention to shape. , 2005, Developmental science.

[14]  Michael C. Hout,et al.  Multidimensional Scaling , 2003, Encyclopedic Dictionary of Archaeology.

[15]  Grigori Yourganov,et al.  The Perception of Naturalness Correlates with Low-Level Visual Features of Environmental Scenes , 2014, PloS one.

[16]  Thomas L. Griffiths,et al.  Latent Features in Similarity Judgments: A Nonparametric Bayesian Approach , 2008, Neural Computation.

[17]  Larissa K. Samuelson,et al.  Online Processing is Essential for Learning: Understanding Fast Mapping and Word Learning in a Dynamic Connectionist Architecture , 2006 .

[18]  A. Grabowska,et al.  The Nencki Affective Picture System (NAPS): Introduction to a novel, standardized, wide-range, high-quality, realistic picture database , 2013, Behavior research methods.

[19]  Michael D. Lee,et al.  Combining Dimensions and Features in Similarity-Based Representations , 2002, NIPS.

[20]  Y Moores.  What's new for children? , 1996, Nursing standard (Royal College of Nursing (Great Britain) : 1987).

[21]  Linda B. Smith,et al.  Infants rapidly learn word-referent mappings via cross-situational statistics , 2008, Cognition.

[22]  Roger N. Shepard,et al.  Additive clustering: Representation of similarities as combinations of discrete overlapping properties. , 1979 .

[23]  R N Shepard,et al.  Multidimensional Scaling, Tree-Fitting, and Clustering , 1980, Science.

[24]  Katherine Twomey,et al.  That's More Like It: Multiple Exemplars Facilitate Word Learning , 2014 .

[25]  David E Warren,et al.  Not so fast: Hippocampal amnesia slows word learning despite successful fast mapping , 2014, Hippocampus.

[26]  Larissa K. Samuelson,et al.  Dynamic Noun Generalization: Moment-to-Moment Interactions Shape Children's Naming Biases. , 2007 .

[27]  Robert L. Goldstone,et al.  Relational similarity and the nonindependence of features in similarity judgments , 1991, Cognitive Psychology.

[28]  A computer-generated face database with ratings on realism, masculinity, race, and stereotypy , 2011, Behavior research methods.

[29]  J. D. Smith,et al.  Distinguishing prototype-based and exemplar-based processes in dot-pattern category learning. , 2002, Journal of experimental psychology. Learning, memory, and cognition.

[30]  Natalie C. Ebner,et al.  FACES—A database of facial expressions in young, middle-aged, and older women and men: Development and validation , 2010, Behavior research methods.

[31]  Michael C Hout,et al.  Incidental learning speeds visual search by lowering response thresholds, not by improving efficiency: evidence from eye movements. , 2012, Journal of experimental psychology. Human perception and performance.

[32]  Larissa K. Samuelson,et al.  The First Slow Step: Differential Effects of Object and Word-Form Familiarization on Retention of Fast-Mapped Words. , 2012, Infancy : the official journal of the International Society on Infant Studies.

[33]  N. Jaworska,et al.  A Review of Multidimensional Scaling (MDS) and its Utility in Various Psychological Domains , 2009 .

[34]  Aude Oliva,et al.  Visual long-term memory has a massive storage capacity for object details , 2008, Proceedings of the National Academy of Sciences.

[35]  Michael C Hout,et al.  Target templates: the precision of mental representations affects attentional guidance and decision-making in visual search , 2015, Attention, perception & psychophysics.

[36]  Larissa K. Samuelson,et al.  What’s new? Children prefer novelty in referent selection , 2011, Cognition.

[37]  Dedre Gentner,et al.  Dedre Gentner A STUDY OF EARLY WORD MEANING USING ARTIFICIAL OBJECTS : WHAT LOOKS LIKE A JIGGY BUT ACTS LIKE A ZIMBO ? , 2004 .

[38]  M. Tarr,et al.  Becoming a “Greeble” Expert: Exploring Mechanisms for Face Recognition , 1997, Vision Research.

[39]  Justin Halberda,et al.  Optimal Contrast: Competition Between Two Referents Improves Word Learning , 2013 .

[40]  Steven J Luck,et al.  Visual short-term memory for complex objects in 6- and 8-month-old infants. , 2014, Child development.

[41]  H. Zimmer,et al.  An action video clip database rated for familiarity in China and Germany , 2012, Behavior research methods.

[42]  G. Schafer,et al.  The impact of novel labels on visual processing during infancy. , 2011, The British journal of developmental psychology.

[43]  Brenda L. Beverly,et al.  Preschool Word Learning During Joint Book Reading , 2004 .

[44]  Brian A. Nosek,et al.  Recommendations for Increasing Replicability in Psychology † , 2013 .

[45]  D. Rakison,et al.  You go this way and I'll go that way: developmental changes in infants' detection of correlations among static and dynamic features in motion events. , 2002, Child development.

[46]  M. Lee,et al.  Common and distinctive features in stimulus similarity: A modified version of the contrast model , 2004, Psychonomic bulletin & review.

[47]  B. McMurray,et al.  Speaker variability augments phonological processing in early word learning. , 2009, Developmental science.

[48]  Willem J. Heiser,et al.  PROXSCAL: A Multidimensional Scaling Program for Individual Differences Scaling with Constraints , 2014 .

[49]  Michael C. Hout,et al.  The versatility of SpAM: a fast, efficient, spatial method of data collection for multidimensional scaling. , 2013, Journal of experimental psychology. General.

[50]  R. Shepard,et al.  Toward a universal law of generalization for psychological science. , 1987, Science.

[51]  D. Gentner,et al.  A cross-linguistic study of early word meaning: universal ontology and linguistic influence , 1997, Cognition.

[52]  E. Markman,et al.  Rapid Word Learning in 13- and 18-Month-Olds. , 1994 .

[53]  Larissa K. Samuelson,et al.  Fast Mapping but Poor Retention by 24-Month-Old Infants. , 2008, Infancy : the official journal of the International Society on Infant Studies.

[54]  Prahlad Gupta,et al.  Does neighborhood density influence repetition latency for nonwords? Separating the effects of density and duration , 2004 .

[55]  Jessica S. Horst.  Context and repetition in word learning , 2013, Front. Psychol..

[56]  N. Kriegeskorte,et al.  Inverse MDS: Inferring Dissimilarity Structure from Multiple Item Arrangements , 2012, Front. Psychology.

[57]  R. Goldstone.  An efficient method for obtaining similarity data , 1994 .

[58]  K. Plunkett,et al.  Learning Words Over Time: The Role of Stimulus Repetition in Mutual Exclusivity. , 2009, Infancy : the official journal of the International Society on Infant Studies.

[59]  Stephen D. Goldinger,et al.  MM-MDS: A Multidimensional Scaling Database with Similarity Ratings for 240 Object Categories from the Massive Memory Picture Database , 2014, PloS one.

[60]  Eleanor Rosch,et al.  Principles of Categorization , 1978 .

[61]  Michael C Hout,et al.  Bogus concerns about the false prototype enhancement effect. , 2011, Journal of experimental psychology. Learning, memory, and cognition.

[62]  E. Spelke,et al.  Perception, ontology, and word meaning , 1992, Cognition.

[63]  Dedre Gentner,et al.  What looks like a jiggy but acts like a zimbo?: A study of early word meaning using artificial objects , 1978 .

[64]  A. Baker,et al.  Rapid learning of minimally different words in five- to six-year-old children: effects of acoustic salience and hearing impairment , 2015, Journal of Child Language.

[65]  Marc H Bornstein,et al.  Experience-based and on-line categorization of objects in early infancy. , 2010, Child development.

[66]  Jessica S. Horst,et al.  Contextual repetition facilitates word learning via fast mapping. , 2014, Acta psychologica.

[67]  Jean Doyen,et al.  Ranks of incidence matrices of Steiner triple systems , 1978 .

[68]  Emma L Axelsson,et al.  Testing a word is not a test of word learning. , 2013, Acta psychologica.

[69]  Timothy F. Brady,et al.  Conceptual Distinctiveness Supports Detailed Visual Long-term Memory for Real-world Objects the Fidelity of Long-term Memory for Visual Information , 2022 .

[70]  Leslie M. Bailey,et al.  Young children and adults use lexical principles to learn New Nouns , 1992 .

[71]  Daniel C. Richardson,et al.  Infants learn about objects from statistics and people. , 2011, Developmental psychology.

[72]  Jessica S. Horst,et al.  It's Taking Shape: Shared Object Features Influence Novel Noun Generalizations. , 2013 .

[73]  A. Tversky.  Features of Similarity , 1977 .

[74]  Catherine M. Sandhofer,et al.  The spacing effect in children’s memory and category induction , 2008, Cognition.

[75]  K. Scherer,et al.  The Geneva affective picture database (GAPED): a new 730-picture database focusing on valence and normative significance , 2011, Behavior research methods.

[76]  Linda B. Smith,et al.  Rapid Word Learning Under Uncertainty via Cross-Situational Statistics , 2007, Psychological science.

[77]  K. Holyoak,et al.  The Oxford handbook of thinking and reasoning , 2012 .