Fritz Günther

Humboldt-Universität zu Berlin | HU Berlin · Department of Psychology

In this article, the R package LSAfun is presented. This package enables a variety of functions and computations based on Vector Semantic Models such as Latent Semantic Analysis (LSA) Landauer, Foltz and Laham (Discourse Processes 25:259-284, 1998), which are procedures to obtain a high-dimensional vector representation for words (and documents) fr...

Models representing meaning as high-dimensional numerical vectors (such as LSA, HAL, BEAGLE, Topic Models, GloVe or word2vec) have been introduced as extremely powerful machine-learning proxies for human semantic representations, and have seen an explosive rise in popularity over the last two decades. However, despite their considerable advancement...

Previous studies found that an automatic meaning-composition process affects the processing of morphologically complex words, and related this operation to conceptual combination. However, research on embodied cognition demonstrates that concepts are more than just lexical meanings, rather being also grounded in perceptual experience. Therefore, pe...

Theories of grounded cognition postulate that concepts are grounded in sensorimotor experience. But how can that be for concepts like Atlantis for which we do not have that experience? We claim that such concepts obtain their sensorimotor grounding indirectly, via already-known concepts used to describe them. Participants learned novel words referr...

Quantitative, data-driven models for mental representations have long enjoyed popularity and success in psychology (e.g., distributional semantic models in the language domain), but have largely been missing for the visual domain. To overcome this, we present ViSpa (Vision Spaces), high-dimensional vector spaces that include vision-based representa...

Valence is a dominant semantic dimension, and it is fundamentally linked to basic approach-avoidance behavior within a broad range of contexts. Previous studies have shown that it is possible to approximate the valence of existing words based on several surface-level and semantic components of the stimuli. Parallelly, recent studies have shown that...

The human body is perhaps the most ubiquitous and salient visual stimulus that we encounter in our daily lives. Given the prevalence of images of human bodies in natural scene statistics, it is no surprise that our mental representations of the body are thought to strongly originate from visual experience. Yet, little is still known about high-leve...

Language processing is influenced by sensorimotor experiences. Here, we review behavioral evidence for embodied and grounded influences in language processing across six linguistic levels of granularity. We examine (a) sub-word features, discussing grounded influences on iconicity (systematic associations between word form and meaning); (b) words,...

The human body is perhaps the most ubiquitous and salient visual stimulus that we encounter in our daily lives. Given the prevalence of images of human bodies in natural scene statistics, it is no surprise that our mental representations of the body are thought to strongly originate from visual experience. Yet, little is still known about high-leve...

Word frequency is one of the best predictors of language processing. Typically, word frequency norms are entirely based on natural-language text data, thus representing what the literature typically refers to as purely linguistic experience. This study presents Flickr frequency norms as a novel word frequency measure from a domain-specific corpus i...

While a number of studies have repeatedly demonstrated an automatic activation of sensorimotor experience during language processing in the form of action-congruency effects, as predicted by theories of grounded cognition, more recent research has not found these effects for words that were just learned from linguistic input alone, without sensorim...

Word frequency is one of the best predictors of language processing. Typically, word frequency norms are entirely based on natural-language text data, thus representing what the literature typically refers to as purely linguistic experience. This study presents Flickr frequency norms as a novel word frequency measure from a domain-specific corpus i...

Large-scale linguistic data is nowadays available in abundance. Using this source of data, previous research has identified redundancies between the statistical structure of natural language and properties of the (physical) world we live in. For example, it has been shown that we can gauge city sizes by analyzing their respective word frequencies i...

Large-scale linguistic data is nowadays available in abundance. Using this source of data, previous research has identified redundancies between the statistical structure of natural language and properties of the (physical) world we live in. For example, it has been shown that we can gauge city sizes by analyzing their respective word frequencies i...

While distributional semantic models that represent word meanings as high-dimensional vectors induced from large text corpora have been shown to successfully predict human behavior across a wide range of tasks, they have also received criticism from different directions. These include concerns over their interpretability (how can numbers specifying...

While distributional semantic models that represent word meanings as high-dimensional vectors induced from large text corpora have been shown to successfully predict human behavior across a wide range of tasks, they have also received criticism from different directions. These include concerns over their interpretability (how can numbers specifying...

While a number of studies have repeatedly demonstrated an automatic activation of sensorimotor experience during language processing in the form of action-congruency effects, as predicted by theories of grounded cognition, more recent research has not found these effects for words that were just learned from linguistic input alone, without sensorim...

Quantitative, data-driven models for mental representations have long enjoyed popularity and success in psychology (for example, distributional semantic models in the language domain), but have largely been missing for the visual domain. To overcome this, we present ViSpa (Vision Spaces), high-dimensional vector spaces that include vision-based rep...

Many theories on the role of semantics in morphological representation and processing focus on the interplay between the lexicalized meaning of the complex word on the one hand, and the individual constituent meanings on the other hand. However, the constituent meaning representations at play do not necessarily correspond to the free-word meanings...

Conversational negation often behaves differently from negation as a logical operator: when rejecting a state of affairs, it does not present all members of the complement set as equally plausible alternatives, but it rather suggests some of them as more plausible than others (e.g., “This is not a dog, it is a wolf/*screwdriver”). Entities that are...

In their strongest formulation, theories of grounded cognition claim that concepts are made up of sensorimotor information. Following such equivalence, perceptual properties of objects should consistently influence processing, even in purely linguistic tasks, where perceptual information is neither solicited nor required. Previous studies have test...

Theories of grounded cognition postulate that concepts are grounded in sensorimotor experience. But how can that be for concepts like Atlantis for which we do not have that experience? We claim that such concepts obtain their sensorimotor grounding indirectly, via already-known concepts used to describe them. Participants learned novel words referr...

In their strongest formulation, theories of grounded cognition claim that concepts are made up of sensorimotor information. Following such equivalence, perceptual properties of objects should consistently influence processing, even in purely linguistic tasks, where perceptual information is neither solicited nor required. Previous studies have test...

Theories of grounded cognition assume that conceptual representations are grounded in sen-sorimotor experience. However, abstract concepts such as jealousy or childhood have no directly associated referents with which such sensorimotor experience can be made; therefore, the grounding of abstract concepts has long been a topic of debate. Here, we pr...

Theories of grounded cognition assume that conceptual representations are grounded in sensorimotor experience. However, abstract concepts such as jealousy or childhood have no directly associated referents with which such sensorimotor experience can be made; therefore, the grounding of abstract concepts has long been a topic of debate. Here, we pro...

While morphemes are theoretically defined as linguistic units linking form and meaning, semantic effects in morphological processing are not reported consistently in the literature on derived and compound words. The lack of consistency in this line of research has often been attributed to methodological differences between studies or contextual eff...

Previous studies found that an automatic meaning-composition process affects the processing of morphologically complex words, and related this operation to conceptual combination. However, research on embodied cognition demonstrates that concepts are more than just lexical meanings, rather being also grounded in perceptual experience. Therefore, pe...

Large-scale linguistic data is nowadays available in abundance. Here, we demonstrate that the surface-level statistical structure of language alone opens a window into how our brain represents the world. To this end, we examine the statistical occurrence of words referring to body parts in very different languages, covering nearly 4 billions of nat...

In the present study, we provide a comprehensive analysis and a multi-dimensional dataset of semantic transparency measures for 1810 German compound words. Compound words are considered semantically transparent when the contribution of the constituents’ meaning to the compound meaning is clear (as in airport), but the degree of semantic transparenc...

Speakers of languages with synchronically productive compounding systems, such as English, are likely to encounter new compounds on a daily basis. These can only be useful for communication if speakers are able to rapidly compose their meanings. However, while compositional meanings can be obtained for some novel compounds such as bridgemill, this...

Speakers of languages with synchronically productive compounding systems, such as English, are likely to encounter new compounds on a daily basis. These can only be useful for communication if speakers are able to rapidly compose their meanings. However, while compositional meanings can be obtained for some novel compounds such as "bridgemill", thi...

In the present study, we provide a comprehensive analysis and a multi-dimensional dataset of semantic transparency measures for 1,810 German compound words. Compound words are considered semantically transparent when the contribution of the constituents’ meaning to the compound meaning is clear (as in airport), but the degree of semantic transparen...

In morphological processing, research has repeatedly found different priming effects by English and German native speakers in the overt priming paradigm. In English, priming effects were found for word pairs with a morphological and semantic relation (SUCCESSFUL-success), but not for pairs without a semantic relation (SUCCESSOR-success). By contras...

In morphological processing, research has repeatedly found different priming effects by English and German native speakers in the overt priming paradigm. In English, priming effects were found for word pairs with a morphological and semantic relation (SUCCESSFUL-success), but not for pairs without a semantic relation (SUCCESSOR-success). By contras...

Effects of semantic transparency, reflected in processing differences between semantically transparent (teabag) and opaque (ladybird) compounds, have received considerable attention in the investigation of the role of constituents in compound processing. However, previous studies have yielded inconsistent results. In the present article, we argue t...

Scoring divergent thinking response sets has always been challenging because such responses are not only open-ended in terms of number of ideas, but each idea may also be expressed by a varying number of concepts and, thus, by a varying number of words (elaboration). While many current studies have attempted to score the semantic distance in diverg...

Theories of embodied cognition assume that concepts are grounded in non-linguistic, sensorimotor experience. In support of this assumption, previous studies have shown that upwards response movements are faster than downwards movements after participants have been presented with words whose referents are typically located in the upper vertical spac...

Noun compounds, consisting of two nouns (the head and the modifier) that are combined into a single concept, differ in terms of their plausibility: school bus is a more plausible compound than saddle olive. The present study investigates which factors influence the plausibility of attested and novel noun compounds. Distributional Semantic Models (D...

In two experiments, we attempted to replicate and extend findings by Günther et al. (2016) that word similarity measures obtained from distributional semantics models—Latent Semantic Analysis (LSA) and Hyperspace Analog to Language (HAL)—predict lexical priming effects. To this end, we used the pseudo-random method to generate item material while s...

Employed Composition Methods. A pre-test comparing different composition methods. (PDF)

Modelling the data. A detailed description of the GAM data analysis. (PDF)

Training Set. The training set used to derive the Modifier Lexical functions. (TXT)

Data Set. The main data set used for the analysis in this study, including the relevant plausibility measures. (TXT)

In distributional semantics models (DSMs) such as latent semantic analysis (LSA), words are represented as vectors in a high-dimensional vector space. This allows for computing word similarities as the cosine of the angle between two such vectors. In two experiments, we investigated whether LSA cosine similarities predict priming effects, in that h...