How Efficiency Shapes Human Language

Non-sentential responses to requests for information

When faced with requests for information ("Where did you go last night?"), why do speakers make non-sentential replies ("The movies") rather than full sentence replies ("I went to the movies")? We examine the role that pragmatic factors (politeness and formality) and memory factors (the speaker's ability to retrieve the answer to the question) play in determining whether speakers generate a non-sentential reply. Participants answered a series of questions about their lives. Pragmatic factors affected the participants' responses. Speakers instructed to be polite or formal made fewer non-sentential replies than speakers who did not receive specific instructions. Memory retrieval (indexed both by the time required for the participant to begin their response and by the presence of disfluencies at the beginning of the response) did not have a straightforward relationship to the production of non-sentential replies. The effect of response latency and disfluencies depended on whether the participants were told to be polite or formal (or if they were given no instruction at all).

Neural populations in the language network differ in the size of their temporal receptive windows

Despite long knowing what brain areas support language comprehension, our knowledge of the neural computations that these frontal and temporal regions implement remains limited. One important unresolved question concerns functional differences among the neural populations that comprise the language network. Here we leveraged the high spatiotemporal resolution of human intracranial recordings (n = 22) to examine responses to sentences and linguistically degraded conditions. We discovered three response profiles that differ in their temporal dynamics. These profiles appear to reflect different temporal receptive windows, with average windows of about 1, 4 and 6 words, respectively. Neural populations exhibiting these profiles are interleaved across the language network, which suggests that all language regions have direct access to distinct, multiscale representations of linguistic input-a property that may be critical for the efficiency and robustness of language processing.

Lingualyzer: A computational linguistic tool for multilingual and multidimensional text analysis

Most natural language models and tools are restricted to one language, typically English. For researchers in the behavioral sciences investigating languages other than English, and for those researchers who would like to make cross-linguistic comparisons, hardly any computational linguistic tools exist, particularly none for those researchers who lack deep computational linguistic knowledge or programming skills. Yet, for interdisciplinary researchers in a variety of fields, ranging from psycholinguistics, social psychology, cognitive psychology, education, to literary studies, there certainly is a need for such a cross-linguistic tool. In the current paper, we present Lingualyzer ( https://lingualyzer.com ), an easily accessible tool that analyzes text at three different text levels (sentence, paragraph, document), which includes 351 multidimensional linguistic measures that are available in 41 different languages. This paper gives an overview of Lingualyzer, categorizes its hundreds of measures, demonstrates how it distinguishes itself from other text quantification tools, explains how it can be used, and provides validations. Lingualyzer is freely accessible for scientific purposes using an intuitive and easy-to-use interface.

Microbial markets: socio-economic perspective in studying microbial communities

Studying microbial communities through a socio-economic lens, this paper draws parallels with human economic transactions and microbes' race for resources. Extending the 'Market Economy' concept of social science to microbial ecosystems, the paper aims to contribute to comprehending the collaborative and competitive dynamics among microorganisms. Created by a multidisciplinary team of an economist, microbiologists, and mathematicians, the paper also highlights the risks involved in employing a socio-economic perspective to explain the complexities of natural ecosystems. Navigating through microbial markets offers insights into the implications of these interactions while emphasizing the need for cautious interpretation within the broader ecological context. We hope that this paper will be a fruitful source of inspiration for future studies on microbial communities.

Even laypeople use legalese

Whereas principles of communicative efficiency and legal doctrine dictate that laws be comprehensible to the common world, empirical evidence suggests legal documents are largely incomprehensible to lawyers and laypeople alike. Here, a corpus analysis (n = 59) million words) first replicated and extended prior work revealing laws to contain strikingly higher rates of complex syntactic structures relative to six baseline genres of English. Next, two preregistered text generation experiments (n = 286) tested two leading hypotheses regarding how these complex structures enter into legal documents in the first place. In line with the magic spell hypothesis, we found people tasked with writing official laws wrote in a more convoluted manner than when tasked with writing unofficial legal texts of equivalent conceptual complexity. Contrary to the copy-and-edit hypothesis, we did not find evidence that people editing a legal document wrote in a more convoluted manner than when writing the same document from scratch. From a cognitive perspective, these results suggest law to be a rare exception to the general tendency in human language toward communicative efficiency. In particular, these findings indicate law's complexity to be derived from its performativity, whereby low-frequency structures may be inserted to signal law's authoritative, world-state-altering nature, at the cost of increased processing demands on readers. From a law and policy perspective, these results suggest that the tension between the ubiquity and impenetrability of the law is not an inherent one, and that laws can be simplified without a loss or distortion of communicative content.

Infant-directed speech becomes less redundant as infants grow: Implications for language learning

Do speakers use less redundant language with more proficient interlocutors? Both the communicative efficiency framework and the language development literature predict that speech directed to younger infants should be more redundant than speech directed to older infants. Here, we test this by quantifying redundancy in infant-directed speech using entropy rate - an information-theoretic measure reflecting average degree of repetitiveness. While IDS is often described as repetitive, entropy rate provides a novel holistic measure of redundancy in this speech genre. Using two developmental corpora, we compare entropy rates of samples taken from different ages. We find that parents use less redundant speech when talking to older children, illustrating an effect of perceived interlocutor proficiency on redundancy. The developmental decrease in redundancy reflects a decrease in lexical repetition, but also a decrease in repetitions of multi-word sequences, highlighting the importance of larger sequences in early language learning.

Good-enough processing, home language proficiency, cognitive skills, and task effects for Korean heritage speakers' sentence comprehension

The present study investigates how heritage speakers conduct good-enough processing at the interface of home-language proficiency, cognitive skills (inhibitory control; working memory), and task types (acceptability judgement; self-paced reading). For this purpose, we employ two word-order patterns (verb-final vs. verb-initial) of two clausal constructions in Korean-suffixal passive and morphological causative-which contrast pertaining to the mapping between thematic roles and case-marking and the interpretive procedures driven by verbal morphology. We find that, while Korean heritage speakers demonstrate the same kind of acceptability-rating behaviour as monolingual Korean speakers do, their reading-time patterns are notably modulated by construction-specific properties, cognitive skills, and proficiency. This suggests a heritage speaker's ability and willingness to conduct both parsing routes, induced by linguistic cues in a non-dominant language, which are proportional to the computational complexity involving these cues. Implications of this study are expected to advance our understanding of a learner's mind for underrepresented languages and populations in the field.

Comparative analyses of the information content of letters, characters, and inter-word spaces across writing systems

One difference among writing systems is how orthographic cues are used to demarcate words; although most alphabetic scripts use inter-word spaces, some Asian scripts do not explicitly mark word boundaries (e.g., Chinese). It is unclear whether these differences are arbitrary or whether they are designed to maximize reading efficiency. Here, we show that spaces inserted between words in non-demarcated scripts provide less information about word boundaries than spaces in demarcated scripts. Furthermore, despite the fact that less information is contained by inter-word spaces than characters/letters of the same size, the information content of inter-word spaces in demarcated scripts is closer to that of characters/letters compared to the information content of inter-word spaces that are inserted in non-demarcated scripts. These results suggest that the conventions used to demarcate word boundaries are sufficient to support efficient reading. Our findings provide new insights into the universals and variation across writing systems and shed light on the mental processes that support skilled reading.

Language is primarily a tool for communication rather than thought

Language is a defining characteristic of our species, but the function, or functions, that it serves has been debated for centuries. Here we bring recent evidence from neuroscience and allied disciplines to argue that in modern humans, language is a tool for communication, contrary to a prominent view that we use language for thinking. We begin by introducing the brain network that supports linguistic ability in humans. We then review evidence for a double dissociation between language and thought, and discuss several properties of language that suggest that it is optimized for communication. We conclude that although the emergence of language has unquestionably transformed human culture, language does not appear to be a prerequisite for complex thought, including symbolic thought. Instead, language is a powerful tool for the transmission of cultural knowledge; it plausibly co-evolved with our thinking and reasoning capacities, and only reflects, rather than gives rise to, the signature sophistication of human cognition.

Phonetic differences between affirmative and feedback head nods in German Sign Language (DGS): A pose estimation study

This study investigates head nods in natural dyadic German Sign Language (DGS) interaction, with the aim of finding whether head nods serving different functions vary in their phonetic characteristics. Earlier research on spoken and sign language interaction has revealed that head nods vary in the form of the movement. However, most claims about the phonetic properties of head nods have been based on manual annotation without reference to naturalistic text types and the head nods produced by the addressee have been largely ignored. There is a lack of detailed information about the phonetic properties of the addressee's head nods and their interaction with manual cues in DGS as well as in other sign languages, and the existence of a form-function relationship of head nods remains uncertain. We hypothesize that head nods functioning in the context of affirmation differ from those signaling feedback in their form and the co-occurrence with manual items. To test the hypothesis, we apply OpenPose, a computer vision toolkit, to extract head nod measurements from video recordings and examine head nods in terms of their duration, amplitude and velocity. We describe the basic phonetic properties of head nods in DGS and their interaction with manual items in naturalistic corpus data. Our results show that phonetic properties of affirmative nods differ from those of feedback nods. Feedback nods appear to be on average slower in production and smaller in amplitude than affirmation nods, and they are commonly produced without a co-occurring manual element. We attribute the variations in phonetic properties to the distinct roles these cues fulfill in turn-taking system. This research underlines the importance of non-manual cues in shaping the turn-taking system of sign languages, establishing the links between such research fields as sign language linguistics, conversational analysis, quantitative linguistics and computer vision.

Redundancy can hinder adult L2 grammar learning: evidence from case markers of varying salience levels

Grammatical redundancy is a widespread feature across languages. Although redundant cues can be seen to increase the complexity and processing burden of structures, it has been suggested that they can assist language acquisition. Here, we explored if this learning benefit can be observed from the very initial stages of second language (L2) acquisition and whether the effect of redundancy is modulated by the perceptual salience of the redundant linguistic cues. Across two experiments, three groups of adult native speakers of English were incidentally exposed to three different artificial languages; one that had a fixed word order, Verb-Object-Subject, and two in which thematic role assignment was additionally determined by a low-salient (Experiment 1) or a high-salient (Experiment 2) redundant case marker. While all groups managed to learn the novel language, our results pointed towards a hindering role of redundancy, with participants in the non-redundant condition achieving greater learning outcomes compared to those in both redundant conditions. Results also revealed that this impeding effect of redundancy on L2 learners can be attenuated by the salience of the redundant cue (Experiment 2). In conjunction with earlier findings, the present results suggest that the effect of redundancy on L2 acquisition can be differentially manifested depending on the stage of L2 development, learners' first language biases and age.

Natural language syntax complies with the free-energy principle

Natural language syntax yields an unbounded array of hierarchically structured expressions. We claim that these are used in the service of active inference in accord with the free-energy principle (FEP). While conceptual advances alongside modelling and simulation work have attempted to connect speech segmentation and linguistic communication with the FEP, we extend this program to the underlying computations responsible for generating syntactic objects. We argue that recently proposed principles of economy in language design-such as "minimal search" criteria from theoretical syntax-adhere to the FEP. This affords a greater degree of explanatory power to the FEP-with respect to higher language functions-and offers linguistics a grounding in first principles with respect to computability. While we mostly focus on building new principled conceptual relations between syntax and the FEP, we also show through a sample of preliminary examples how both tree-geometric depth and a Kolmogorov complexity estimate (recruiting a Lempel-Ziv compression algorithm) can be used to accurately predict legal operations on syntactic workspaces, directly in line with formulations of variational free energy minimization. This is used to motivate a general principle of language design that we term Turing-Chomsky Compression (TCC). We use TCC to align concerns of linguists with the normative account of self-organization furnished by the FEP, by marshalling evidence from theoretical linguistics and psycholinguistics to ground core principles of efficient syntactic computation within active inference.

Vagueness as an implicit-encoding persuasive strategy: an experimental approach

The paper provides novel theoretical and experimental perspectives on the functioning of linguistic vagueness as an implicit persuasive strategy. It presents an operative definition of pragmatically marked vagueness, referring to vague expressions whose interpretation is not retrievable by recipients. The phenomenon is illustrated via numerous examples of its use in predominantly persuasive texts (i.e., advertising and political propaganda) in different languages. The psycholinguistic functioning of vague expressions is then illustrated by the results of a self-paced reading task experiment. Data showing shorter reading times associated with markedly vague expressions as compared to expressions that are either (a) lexically more precise or (b) made precise by the context suggest that the former are interpreted in a shallow way, without searching for and/or retrieving exact referents. These results support the validity of a differentiation between context-supported vs. non-supported vague expressions. Furthermore, validation of using marked vagueness as a persuasive implicit strategy which reduces epistemic vigilance is provided.

Color sorting and color term evolution

When participants sort color samples into piles, Boster showed that their color groupings can resemble the "stages" of Kay & McDaniel's model of color term evolution. Boster concluded that both the unfolding of color piles in a sequential color sorting task and the unfolding of color terms according to Kay & McDaniel's model reveal how human beings understand color. If this is correct, then: (1) pile sorts should be reasonably robust across variations in the palette of colors to be sorted, as long as the palette contains good examples of Berlin & Kay's universal color categories, and (2) pile-sorting should be more related to lexical effects and less related to perceptual processes governed by similarity judgments alone. We report three studies on English speakers and Somali speakers (Study 1 only), where participants sorted colors into 2…6 piles. The three studies used varying numbers of palette colors (25, 30, or 145 colors) and varying chromaticity schemes (mainly hue, widely-separated in hue and lightness, or densely distributed at high chroma). We compared human sorting behavior to Kay & McDaniel's model and to the "optimal" patterns of color sorting predicted by Regier's well-formedness statistic, which quantifies the perceived similarity between colors. Neither hypothesis is confirmed by the results of our studies. Thus, we propose that color sorts are determined by pragmatic influences based on heuristics that are inspired by the palette of colors that are available and the task that the viewer is asked to perform.

Language-like efficiency and structure in house finch song

Communication needs to be complex enough to be functional while minimizing learning and production costs. Recent work suggests that the vocalizations and gestures of some songbirds, cetaceans and great apes may conform to linguistic laws that reflect this trade-off between efficiency and complexity. In studies of non-human communication, though, clustering signals into types cannot be done a priori, and decisions about the appropriate grain of analysis may affect statistical signals in the data. The aim of this study was to assess the evidence for language-like efficiency and structure in house finch (Haemorhous mexicanus) song across three levels of granularity in syllable clustering. The results show strong evidence for Zipf's rank-frequency law, Zipf's law of abbreviation and Menzerath's law. Additional analyses show that house finch songs have small-world structure, thought to reflect systematic structure in syntax, and the mutual information decay of sequences is consistent with a combination of Markovian and hierarchical processes. These statistical patterns are robust across three levels of granularity in syllable clustering, pointing to a limited form of scale invariance. In sum, it appears that house finch song has been shaped by pressure for efficiency, possibly to offset the costs of female preferences for complexity.

Systematic mappings of sound to meaning: A theoretical review

The form of a word sometimes conveys semantic information. For example, the iconic word gurgle sounds like what it means, and busy is easy to identify as an English adjective because it ends in -y. Such links between form and meaning matter because they help people learn and use language. But gurgle also sounds like gargle and burble, and the -y in busy is morphologically and etymologically unrelated to the -y in crazy and watery. Whatever processing effects gurgle and busy have in common likely stem not from iconic, morphological, or etymological relationships but from systematicity more broadly: the phenomenon whereby semantically related words share a phonological or orthographic feature. In this review, we evaluate corpus evidence that spoken languages are systematic (even when controlling for iconicity, morphology, and etymology) and experimental evidence that systematicity impacts word processing (even in lieu of iconic, morphological, and etymological relationships). We conclude by drawing attention to the relationship between systematicity and low-frequency words and, consequently, the role that systematicity plays in natural language processing.

Surprisal From Language Models Can Predict ERPs in Processing Predicate-Argument Structures Only if Enriched by an Agent Preference Principle

Language models based on artificial neural networks increasingly capture key aspects of how humans process sentences. Most notably, model-based surprisals predict event-related potentials such as N400 amplitudes during parsing. Assuming that these models represent realistic estimates of human linguistic experience, their success in modeling language processing raises the possibility that the human processing system relies on no other principles than the general architecture of language models and on sufficient linguistic input. Here, we test this hypothesis on N400 effects observed during the processing of verb-final sentences in German, Basque, and Hindi. By stacking Bayesian generalised additive models, we show that, in each language, N400 amplitudes and topographies in the region of the verb are best predicted when model-based surprisals are complemented by an Agent Preference principle that transiently interprets initial role-ambiguous noun phrases as agents, leading to reanalysis when this interpretation fails. Our findings demonstrate the need for this principle independently of usage frequencies and structural differences between languages. The principle has an unequal force, however. Compared to surprisal, its effect is weakest in German, stronger in Hindi, and still stronger in Basque. This gradient is correlated with the extent to which grammars allow unmarked NPs to be patients, a structural feature that boosts reanalysis effects. We conclude that language models gain more neurobiological plausibility by incorporating an Agent Preference. Conversely, theories of human processing profit from incorporating surprisal estimates in addition to principles like the Agent Preference, which arguably have distinct evolutionary roots.

History constrains the evolution of efficient color naming, enabling historical inference

Color naming in natural languages is not arbitrary: It reflects efficient partitions of perceptual color space [T. Regier, P. Kay, N. Khetarpal, Proc. Natl. Acad. Sci. U.S.A. 104, 1436-1441 (2007)] modulated by the relative needs to communicate about different colors [C. Twomey, G. Roberts, D. Brainard, J. Plotkin, Proc. Natl. Acad. Sci. U.S.A. 118, e2109237118 (2021)]. These psychophysical and communicative constraints help explain why languages around the world have remarkably similar, but not identical, mappings of colors to color terms. Languages converge on a small set of efficient representations.But languages also evolve, and the number of terms in a color vocabulary may change over time. Here we show that history, i.e. the existence of an antecedent color vocabulary, acts as a nonadaptive constraint that biases the choice of efficient solution as a language transitions from a vocabulary of size [Formula: see text] to [Formula: see text] terms. Moreover, as efficient vocabularies evolve to include more terms they explore a smaller fraction of all possible efficient vocabularies compared to equally sized vocabularies constructed de novo. This path dependence of the cultural evolution of color naming presents an opportunity. Historical constraints can be used to reconstruct ancestral color vocabularies, allowing us to answer long-standing questions about the evolutionary sequences of color words, and enabling us to draw inferences from phylogenetic patterns of language change.

Signal Smoothing and Syntactic Choices: A Critical Reflection on the UID Hypothesis

The Smooth Signal Redundancy Hypothesis explains variations in syllable length as a means to more uniformly distribute information throughout the speech signal. The Uniform Information Density hypothesis seeks to generalize this to choices on all linguistic levels, particularly syntactic choices. While there is some evidence for the Uniform Information Density hypothesis, it faces several challenges, four of which are discussed in this paper. First, it is not clear what exactly counts as uniform. Second, there are syntactic alternations that occur systematically but that can cause notable fluctuations in the information signature. Third, there is an increasing body of negative results. Fourth, there is a lack of large-scale evidence. As to the fourth point, this paper provides a broader array of data-936 sentence pairs for nine syntactic constructions-and analyzes them in a test setup that treats the hypothesis as a classifier. For our data, the Uniform Information Density hypothesis showed little predictive capacity. We explore ways to reconcile our data with theory.

Cultural evolution creates the statistical structure of language

Human language is unique in its structure: language is made up of parts that can be recombined in a productive way. The parts are not given but have to be discovered by learners exposed to unsegmented wholes. Across languages, the frequency distribution of those parts follows a power law. Both statistical properties-having parts and having them follow a particular distribution-facilitate learning, yet their origin is still poorly understood. Where do the parts come from and why do they follow a particular frequency distribution? Here, we show how these two core properties emerge from the process of cultural evolution with whole-to-part learning. We use an experimental analog of cultural transmission in which participants copy sets of non-linguistic sequences produced by a previous participant: This design allows us to ask if parts will emerge purely under pressure for the system to be learnable, even without meanings to convey. We show that parts emerge from initially unsegmented sequences, that their distribution becomes closer to a power law over generations, and, importantly, that these properties make the sets of sequences more learnable. We argue that these two core statistical properties of language emerge culturally both as a cause and effect of greater learnability.

Elliptical Responses to Direct and Indirect Requests for Information

We present two studies examining the factors that lead speakers to produce elliptical responses to requests for information. Following Clark and Levelt and Kelter, experimenters called businesses and asked about their closing time (e.g., Can you tell me what time you close?). Participants provided the requested information in full sentence responses (We close at 9) or elliptical responses (At 9). A reanalysis of data from previous experiments using this paradigm shows that participants are more likely to produce an elliptical response when the question is a direct request for information (What time do you close?) than when the question is an indirect request for information (Can you tell me what time you close?). Participants were less likely to produce an elliptical response when they began their answer by providing a yes/no response (e.g., Sure . . . we close at 9). A new experiment replicated these findings, and further showed that elliptical responses were less likely when (1) irrelevant linguistic content was inserted between the question and the participant's response, and (2) participants verbalized signs of difficulty retrieving the requested information. This latter effect is most prominent in response to questions that are seen as very polite (May I ask you what time you close?). We discuss the role that the recoverability of the intended meaning of the ellipsis, the accessibility of potential antecedents for the ellipsis, pragmatic factors, and memory retrieval play in shaping the production of ellipsis.

Human languages with greater information density have higher communication speed but lower conversation breadth

Human languages vary widely in how they encode information within circumscribed semantic domains (for example, time, space, colour, human body parts and activities), but little is known about the global structure of semantic information and nothing about its relation to human communication. We first show that across a sample of ~1,000 languages, there is broad variation in how densely languages encode information into words. Second, we show that this language information density is associated with a denser configuration of semantic information. Finally, we trace the relationship between language information density and patterns of communication, showing that informationally denser languages tend towards faster communication but conceptually narrower conversations or expositions within which topics are discussed at greater depth. These results highlight an important source of variation across the human communicative channel, revealing that the structure of language shapes the nature and texture of human engagement, with consequences for human behaviour across levels of society.

Effects of linguistic context and noise type on speech comprehension

Introduction

Understanding speech in background noise is an effortful endeavor. When acoustic challenges arise, linguistic context may help us fill in perceptual gaps. However, more knowledge is needed regarding how different types of background noise affect our ability to construct meaning from perceptually complex speech input. Additionally, there is limited evidence regarding whether perceptual complexity (e.g., informational masking) and linguistic complexity (e.g., occurrence of contextually incongruous words) interact during processing of speech material that is longer and more complex than a single sentence. Our first research objective was to determine whether comprehension of spoken sentence pairs is impacted by the informational masking from a speech masker. Our second objective was to identify whether there is an interaction between perceptual and linguistic complexity during speech processing.

Methods

We used multiple measures including comprehension accuracy, reaction time, and processing effort (as indicated by task-evoked pupil response), making comparisons across three different levels of linguistic complexity in two different noise conditions. Context conditions varied by final word, with each sentence pair ending with an expected exemplar (EE), within-category violation (WV), or between-category violation (BV). Forty young adults with typical hearing performed a speech comprehension in noise task over three visits. Each participant heard sentence pairs presented in either multi-talker babble or spectrally shaped steady-state noise (SSN), with the same noise condition across all three visits.

Results

We observed an effect of context but not noise on accuracy. Further, we observed an interaction of noise and context in peak pupil dilation data. Specifically, the context effect was modulated by noise type: context facilitated processing only in the more perceptually complex babble noise condition.

Discussion

These findings suggest that when perceptual complexity arises, listeners make use of the linguistic context to facilitate comprehension of speech obscured by background noise. Our results extend existing accounts of speech processing in noise by demonstrating how perceptual and linguistic complexity affect our ability to engage in higher-level processes, such as construction of meaning from speech segments that are longer than a single sentence.

Cognitive Science From the Perspective of Linguistic Diversity

This letter addresses two issues in language research that are important to cognitive science: the comparability of word meanings across languages and the neglect of an integrated approach to writing systems. The first issue challenges generativist claims by emphasizing the importance of comparability of data, drawing on typologists' findings about different languages. The second issue addresses the exclusion of diverse writing systems from linguistic investigation and argues for a more extensive study of their effects on language and cognition. We argue for a refocusing of cognitive science research on linguistic diversity in all modalities to develop the most robust understanding of language and its role in human cognition more broadly.

Interactive repair and the foundations of language

The robustness and flexibility of human language is underpinned by a machinery of interactive repair. Repair is deeply intertwined with two core properties of human language: reflexivity (it can communicate about itself) and accountability (it is used to publicly enforce social norms). We review empirical and theoretical advances from across the cognitive sciences that mark interactive repair as a domain of pragmatic universals, a key place to study metacognition in interaction, and a system that enables collective computation. This provides novel insights into the role of repair in comparative cognition, language development, and human-computer interaction. As an always-available fallback option and an infrastructure for negotiating social commitments, interactive repair is foundational to the resilience, complexity, and flexibility of human language.

Creating ad hoc graphical representations of number

The ability to communicate about exact number is critical to many modern human practices spanning science, industry, and politics. Although some early numeral systems used 1-to-1 correspondence (e.g., 'IIII' to represent 4), most systems provide compact representations via more arbitrary conventions (e.g., '7' and 'VII'). When people are unable to rely on conventional numerals, however, what strategies do they initially use to communicate number? Across three experiments, participants used pictures to communicate about visual arrays of objects containing 1-16 items, either by producing freehand drawings or combining sets of visual tokens. We analyzed how the pictures they produced varied as a function of communicative need (Experiment 1), spatial regularities in the arrays (Experiment 2), and visual properties of tokens (Experiment 3). In Experiment 1, we found that participants often expressed number in the form of 1-to-1 representations, but sometimes also exploited the configuration of sets. In Experiment 2, this strategy of using configural cues was exaggerated when sets were especially large, and when the cues were predictably correlated with number. Finally, in Experiment 3, participants readily adopted salient numerical features of objects (e.g., four-leaf clover) and generally combined them in a cumulative-additive manner. Taken together, these findings corroborate historical evidence that humans exploit correlates of number in the external environment - such as shape, configural cues, or 1-to-1 correspondence - as the basis for innovating more abstract number representations.

Concepts Are Restructured During Language Contact: The Birth of Blue and Other Color Concepts in Tsimane'-Spanish Bilinguals

Words and the concepts they represent vary across languages. Here we ask if mother-tongue concepts are altered by learning a second language. What happens when speakers of Tsimane', a language with few consensus color terms, learn Bolivian Spanish, a language with more terms? Three possibilities arise: Concepts in Tsimane' may remain unaffected, or they may be remapped, either by Tsimane' terms taking on new meanings or by borrowing Bolivian-Spanish terms. We found that adult bilingual speakers (n = 30) remapped Tsimane' concepts without importing Bolivian-Spanish terms into Tsimane'. All Tsimane' terms become more precise; for example, concepts of monolingual shandyes and yụshñus (~green or blue, used synonymously by Tsimane' monolinguals; n = 71) come to reflect the Bolivian-Spanish distinction of verde (~green) and azul (~blue). These results show that learning a second language can change the concepts in the first language.

Psychological Impact of Languages on the Human Mind: Research on the Contribution of Psycholinguistics Approach to Teaching and Learning English

Language is one of the essential elements of communication. Learning some common language can help people overcome language barriers between people from different countries. English is one of the common languages and it helps individuals adapt to the modern world. Learning the English language is beneficial through teaching methods developed based on Psycholinguistics principles. Four languages are taught by the approach of psycholinguistics that are (to listen, to read, to write and to speak).Psycholinguistics is the integration of psychology (the study of the mind) and linguistics (the study of language). Hence, Psycholinguistics is the study of mind and language. It investigates the procedure taking place in the brain while the perception and creation of language. It studies the psychological impact of languages on the human mind. Recent research focuses on Psycholinguistics theories and talks over the significant impact of psycholinguistics techniques in English Language studying and training. Psycholinguistic studies are based on various ways of responding in a fundamental way and are based on evidence. This study contributes to our understanding of the importance of psychological approaches in teaching and learning English.

Grammatical cues to subjecthood are redundant in a majority of simple clauses across languages

Grammatical cues are sometimes redundant with word meanings in natural language. For instance, English word order rules constrain the word order of a sentence like "The dog chewed the bone" even though the status of "dog" as subject and "bone" as object can be inferred from world knowledge and plausibility. Quantifying how often this redundancy occurs, and how the level of redundancy varies across typologically diverse languages, can shed light on the function and evolution of grammar. To that end, we performed a behavioral experiment in English and Russian and a cross-linguistic computational analysis measuring the redundancy of grammatical cues in transitive clauses extracted from corpus text. English and Russian speakers (n = 484) were presented with subjects, verbs, and objects (in random order and with morphological markings removed) extracted from naturally occurring sentences and were asked to identify which noun is the subject of the action. Accuracy was high in both languages (∼89% in English, ∼87% in Russian). Next, we trained a neural network machine classifier on a similar task: predicting which nominal in a subject-verb-object triad is the subject. Across 30 languages from eight language families, performance was consistently high: a median accuracy of 87%, comparable to the accuracy observed in the human experiments. The conclusion is that grammatical cues such as word order are necessary to convey subjecthood and objecthood in a minority of naturally occurring transitive clauses; nevertheless, they can (a) provide an important source of redundancy and (b) are crucial for conveying intended meaning that cannot be inferred from the words alone, including descriptions of human interactions, where roles are often reversible (e.g., Ray helped Lu/Lu helped Ray), and expressing non-prototypical meanings (e.g., "The bone chewed the dog.").

Event Knowledge in Large Language Models: The Gap Between the Impossible and the Unlikely

Word co-occurrence patterns in language corpora contain a surprising amount of conceptual knowledge. Large language models (LLMs), trained to predict words in context, leverage these patterns to achieve impressive performance on diverse semantic tasks requiring world knowledge. An important but understudied question about LLMs' semantic abilities is whether they acquire generalized knowledge of common events. Here, we test whether five pretrained LLMs (from 2018's BERT to 2023's MPT) assign a higher likelihood to plausible descriptions of agent-patient interactions than to minimally different implausible versions of the same event. Using three curated sets of minimal sentence pairs (total n = 1215), we found that pretrained LLMs possess substantial event knowledge, outperforming other distributional language models. In particular, they almost always assign a higher likelihood to possible versus impossible events (The teacher bought the laptop vs. The laptop bought the teacher). However, LLMs show less consistent preferences for likely versus unlikely events (The nanny tutored the boy vs. The boy tutored the nanny). In follow-up analyses, we show that (i) LLM scores are driven by both plausibility and surface-level sentence features, (ii) LLM scores generalize well across syntactic variants (active vs. passive constructions) but less well across semantic variants (synonymous sentences), (iii) some LLM errors mirror human judgment ambiguity, and (iv) sentence plausibility serves as an organizing dimension in internal LLM representations. Overall, our results show that important aspects of event knowledge naturally emerge from distributional linguistic patterns, but also highlight a gap between representations of possible/impossible and likely/unlikely events.

An information-theoretic approach to the typology of spatial demonstratives

We explore systems of spatial deictic words (such as 'here' and 'there') from the perspective of communicative efficiency using typological data from over 200 languages Nintemann et al. (2020). We argue from an information-theoretic perspective that spatial deictic systems balance informativity and complexity in the sense of the Information Bottleneck (Zaslavsky et al., (2018). We find that under an appropriate choice of cost function and need probability over meanings, among all the 21,146 theoretically possible spatial deictic systems, those adopted by real languages lie near an efficient frontier of informativity and complexity. Moreover, we find that the conditions that the need probability and the cost function need to satisfy for this result are consistent with the cognitive science literature on spatial cognition, especially regarding the source-goal asymmetry. We further show that the typological data are better explained by introducing a notion of consistency into the Information Bottleneck framework, which is jointly optimized along with informativity and complexity.

Expectations of Processing Ease, Informativeness, and Accuracy Guide Toddlers' Processing of Novel Communicative Cues

Discovering the meaning of novel communicative cues is challenging and amounts to navigating an unbounded hypothesis space. Several theories posit that this problem can be simplified by relying on positive expectations about the cognitive utility of communicated information. These theories imply that learners should assume that novel communicative cues tend to have low processing costs and high cognitive benefits. We tested this hypothesis in three studies in which toddlers (N = 90) searched for a reward hidden in one of several containers. In all studies, an adult communicated the reward's location with an unfamiliar and ambiguous cue. We manipulated the processing costs (operationalized as inferential chain length) and cognitive benefits (operationalized as informativeness) of the possible interpretations of the cues. Toddlers processing of novel communicative cues were guided by expectations of low processing costs (Study 1) and high cognitive benefits (Studies 2 and 3). More specifically, toddlers treated novel cues as if they were easy to process, informative, and accurate, even when provided with repeated evidence to the contrary. These results indicate that, from toddlerhood onward, expectations of cognitive utility shape the processing of novel communicative cues. These data also reveal that toddlers, who are in the process of learning the language and communicative conventions of people around them, exert a pressure favoring cognitive efficiency in communicative systems.

Languages with more speakers tend to be harder to (machine-)learn

Computational language models (LMs), most notably exemplified by the widespread success of OpenAI's ChatGPT chatbot, show impressive performance on a wide range of linguistic tasks, thus providing cognitive science and linguistics with a computational working model to empirically study different aspects of human language. Here, we use LMs to test the hypothesis that languages with more speakers tend to be easier to learn. In two experiments, we train several LMs-ranging from very simple n-gram models to state-of-the-art deep neural networks-on written cross-linguistic corpus data covering 1293 different languages and statistically estimate learning difficulty. Using a variety of quantitative methods and machine learning techniques to account for phylogenetic relatedness and geographical proximity of languages, we show that there is robust evidence for a relationship between learning difficulty and speaker population size. However, contrary to expectations derived from previous research, our results suggest that languages with more speakers tend to be harder to learn.

Questions About Quantifiers: Symbolic and Nonsymbolic Quantity Processing by the Brain

One approach to understanding how the human cognitive system stores and operates with quantifiers such as "some," "many," and "all" is to investigate their interaction with the cognitive mechanisms for estimating and comparing quantities from perceptual input (i.e., nonsymbolic quantities). While a potential link between quantifier processing and nonsymbolic quantity processing has been considered in the past, it has never been discussed extensively. Simultaneously, there is a long line of research within the field of numerical cognition on the relationship between processing exact number symbols (such as "3" or "three") and nonsymbolic quantity. This accumulated knowledge can potentially be harvested for research on quantifiers since quantifiers and number symbols are two different ways of referring to quantity information symbolically. The goal of the present review is to survey the research on the relationship between quantifiers and nonsymbolic quantity processing mechanisms and provide a set of research directions and specific questions for the investigation of quantifier processing.

Studying Psychosis Using Natural Language Generation: A Review of Emerging Opportunities

Disrupted language in psychotic disorders, such as schizophrenia, can manifest as false contents and formal deviations, often described as thought disorder. These features play a critical role in the social dysfunction associated with psychosis, but we continue to lack insights regarding how and why these symptoms develop. Natural language generation (NLG) is a field of computer science that focuses on generating human-like language for various applications. The theory that psychosis is related to the evolution of language in humans suggests that NLG systems that are sufficiently evolved to generate human-like language may also exhibit psychosis-like features. In this conceptual review, we propose using NLG systems that are at various stages of development as in silico tools to study linguistic features of psychosis. We argue that a program of in silico experimental research on the network architecture, function, learning rules, and training of NLG systems can help us understand better why thought disorder occurs in patients. This will allow us to gain a better understanding of the relationship between language and psychosis and potentially pave the way for new therapeutic approaches to address this vexing challenge.

Scale in Language

A central concern of the cognitive science of language since its origins has been the concept of the linguistic system. Recent approaches to the system concept in language point to the exceedingly complex relations that hold between many kinds of interdependent systems, but it can be difficult to know how to proceed when "everything is connected." This paper offers a framework for tackling that challenge by identifying *scale* as a conceptual mooring for the interdisciplinary study of language systems. The paper begins by defining the scale concept-simply, the possibility for a measure to be larger or smaller in different instances of a system, such as a phonemic inventory, a word's frequency value in a corpus, or a speaker population. We review sites of scale difference in and across linguistic subsystems, drawing on findings from linguistic typology, grammatical description, morphosyntactic theory, psycholinguistics, computational corpus work, and social network demography. We consider possible explanations for scaling differences and constraints in language. We then turn to the question of *dependencies between* sites of scale difference in language, reviewing four sample domains of scale dependency: in phonological systems, across levels of grammatical structure (Menzerath's Law), in corpora (Zipf's Law and related issues), and in speaker population size. Finally, we consider the implications of the review, including the utility of a scale framework for generating new questions and inspiring methodological innovations and interdisciplinary collaborations in cognitive-scientific research on language.

Information-theoretic principles in incremental language production

I apply a recently emerging perspective on the complexity of action selection, the rate-distortion theory of control, to provide a computational-level model of errors and difficulties in human language production, which is grounded in information theory and control theory. Language production is cast as the sequential selection of actions to achieve a communicative goal subject to a capacity constraint on cognitive control. In a series of calculations, simulations, corpus analyses, and comparisons to experimental data, I show that the model directly predicts some of the major known qualitative and quantitative phenomena in language production, including semantic interference and predictability effects in word choice; accessibility-based ("easy-first") production preferences in word order alternations; and the existence and distribution of disfluencies including filled pauses, corrections, and false starts. I connect the rate-distortion view to existing models of human language production, to probabilistic models of semantics and pragmatics, and to proposals for controlled language generation in the machine learning and reinforcement learning literature.

The color communication game

There is clear diversity among speakers of a typical language in how colors are named. What is the impact of this diversity on the people's ability to communicate about color? Is there a gap between a person's general understanding of the color terms in their native language and how they understand a particular term that denotes a particular color sample? Seventy English-speaking dyads and 63 Somali-speaking dyads played the Color Communication Game, where the "sender" in each dyad named 30 color samples as they would in any color-naming study, then the "receiver" chose the sample they thought the sender intended to communicate. English speakers played again, under instructions to intentionally communicate color sample identity. Direct comparison of senders' samples and receivers' choices revealed categorical understanding of colors without considering color naming data. Although Somali-speaking senders provided fewer color terms, interpersonal Mutual Information (MI) calculated from color naming data was similarly below optimal for both groups, and English-speaking dyads' MI did not improve with experience. Both groups revealed superior understanding of color terms because receivers showed better exactly-correct selection performance than was predicted by simulation from their senders' color-naming data. This study highlights limitations on information-theoretic analyses of color naming data.

A large quantitative analysis of written language challenges the idea that all languages are equally complex

One of the fundamental questions about human language is whether all languages are equally complex. Here, we approach this question from an information-theoretic perspective. We present a large scale quantitative cross-linguistic analysis of written language by training a language model on more than 6500 different documents as represented in 41 multilingual text collections consisting of ~ 3.5 billion words or ~ 9.0 billion characters and covering 2069 different languages that are spoken as a native language by more than 90% of the world population. We statistically infer the entropy of each language model as an index of what we call average prediction complexity. We compare complexity rankings across corpora and show that a language that tends to be more complex than another language in one corpus also tends to be more complex in another corpus. In addition, we show that speaker population size predicts entropy. We argue that both results constitute evidence against the equi-complexity hypothesis from an information-theoretic perspective.

Gaps in the Lexicon Restrict Communication

Across languages, words carve up the world of experience in different ways. For example, English lacks an equivalent to the Chinese superordinate noun tiáowèipǐn, which is loosely translated as "ingredients used to season food while cooking." Do such differences matter? A conventional label may offer a uniquely effective way of communicating. On the other hand, lexical gaps may be easily bridged by the compositional power of language. After all, most of the ideas we want to express do not map onto simple lexical forms. We conducted a referential Director/Matcher communication task with adult speakers of Chinese and English. Directors provided a clue that Matchers used to select words from a word grid. The three target words corresponded to a superordinate term (e.g., beverages) in either Chinese or English but not both. We found that Matchers were more accurate at choosing the target words when their language lexicalized the target category. This advantage was driven entirely by the Directors' use/non-use of the intended superordinate term. The presence of a conventional superordinate had no measurable effect on speakers' within- or between-category similarity ratings. These results show that the ability to rely on a conventional term is surprisingly important despite the flexibility languages offer to communicate about non-lexicalized categories.

Even lawyers do not like legalese

Across modern civilization, societal norms and rules are established and communicated largely in the form of written laws. Despite their prevalence and importance, legal documents have long been widely acknowledged to be difficult to understand for those who are required to comply with them (i.e., everyone). Why? Across two preregistered experiments, we evaluated five hypotheses for why lawyers write in a complex manner. Experiment 1 revealed that lawyers, like laypeople, were less able to recall and comprehend legal content drafted in a complex "legalese" register than content of equivalent meaning drafted in a simplified register. Experiment 2 revealed that lawyers rated simplified contracts as equally enforceable as legalese contracts, and rated simplified contracts as preferable to legalese contracts on several dimensions-including overall quality, appropriateness of style, and likelihood of being signed by a client. These results suggest that lawyers who write in a convoluted manner do so as a matter of convenience and tradition as opposed to an outright preference and that simplifying legal documents would be both tractable and beneficial for lawyers and nonlawyers alike.

Universality, domain-specificity, and development of psychological responses to music

Humans can find music happy, sad, fearful, or spiritual. They can be soothed by it or urged to dance. Whether these psychological responses reflect cognitive adaptations that evolved expressly for responding to music is an ongoing topic of study. In this Review, we examine three features of music-related psychological responses that help to elucidate whether the underlying cognitive systems are specialized adaptations: universality, domain-specificity, and early expression. Focusing on emotional and behavioural responses, we find evidence that the relevant psychological mechanisms are universal and arise early in development. However, the existing evidence cannot establish that these mechanisms are domain-specific. To the contrary, many findings suggest that universal psychological responses to music reflect more general properties of emotion, auditory perception, and other human cognitive capacities that evolved for non-musical purposes. Cultural evolution, driven by the tinkering of musical performers, evidently crafts music to compellingly appeal to shared psychological mechanisms, resulting in both universal patterns (such as form-function associations) and culturally idiosyncratic styles.

Head and dependent marking and dependency length in possessive noun phrases: a typological study of morphological and syntactic complexity

The interaction of morphosyntactic features has been of great interest in research on linguistic complexity. In this paper we approach such interactions in possessive noun phrases. First, we study the interaction of head marking and dependent marking in this domain with typological feature data and with multilingual corpus data. The data suggest that there is a clear inverse relationship between head and dependent marking in possessive noun phrases in terms of complexity. The result points to evidence on complexity trade-offs and to productive integration of typological and corpus-based approaches. Second, we explore whether zero versus overt morphological marking as a measure of morphological complexity affects dependency length as a measure of syntactic complexity. Data from multilingual corpora suggest that there is no cross-linguistic trend between these measures in possessive noun phrases.

Quantifiers satisfying semantic universals have shorter minimal description length

Despite wide variation among natural languages, there are linguistic properties thought to be universal to all or nearly all languages. Here, we consider universals at the semantic level, in the domain of quantifiers, which are given by the properties of monotonicity, quantity, and conservativity, and we investigate whether these universals might be explained by differences in complexity. First, we use a minimal pair methodology and compare the complexities of individual quantifiers using approximate Kolmogorov complexity. Second, we use a simple yet expressive grammar to generate a large collection of quantifiers and we investigate their complexities at an aggregate level in terms of both their minimal description lengths and their approximate Kolmogorov complexities. For minimal description length we find that quantifiers satisfying semantic universals are simpler: they have a shorter minimal description length. For approximate Kolmogorov complexity we find that monotone quantifiers have a lower Kolmogorov complexity than non-monotone quantifiers and for quantity and conservativity we find that approximate Kolmogorov complexity does not scale robustly. These results suggest that the simplicity of quantifier meanings, in terms of their minimal description length, partially explains the presence of semantic universals in the domain of quantifiers.

Informativeness across Interpreting Types: Implications for Language Shifts under Cognitive Load

Previous quantitative studies discussing interpreting types have focused on various features of linguistic forms in outputs. However, none of them has examined their informativeness. Entropy, as a measure of the average information content and the uniformity of the probability distribution of language units, has been applied to quantitative linguistic research on different types of language texts. In the present study, entropy and repeat rate were used to investigate the difference of overall informativeness and concentration of output texts between simultaneous interpreting and consecutive interpreting. We intend to figure out the frequency distribution patterns of word and word category in two types of interpreting texts. Analyses of linear mixed-effects models showed that entropy and repeat rate can distinguish the informativeness of consecutive and simultaneous interpreting outputs, and consecutive interpreting outputs entail a higher word entropy value and a lower word repeat rate than simultaneous interpreting outputs. We propose that consecutive interpreting is a cognitive process which reaches an equilibrium between production economy for interpreters and comprehension sufficiency for listeners, especially in the case where input speeches are more complex. Our findings also shed lights on the selection of interpreting types in application scenarios. The current research is the first of its kind in examining informativeness across interpreting types, demonstrating a dynamic adaptation of language users to extreme cognitive load.

How infants' utterances grow: A probabilistic account of early language development

Why are children's first utterances short and ungrammatical, with some obvious constructions missing? What determines the lengthening of children's early utterances over time? The literature is replete with references to a one-word, a two-word, and a later multiword stage in language development, but with little empirical evidence, and with little account for how and why utterances grow. To address these questions, we analyze speech samples from 25 children between the ages of 14 and 43 months; we construct distributions of their utterances of lengths one to five by age. Our novel findings are that multiword utterances of different lengths appear early in acquisition and increase together until they reach relatively stable proportions similar to those found in parents' input. To explain such patterns, we develop a probabilistic computational model, VIRTUAL, that posits an interaction between a) varying, increasing resources from various developmental domains and b) target utterance lengths mirroring the input. VIRTUAL successfully accounts for most of the empirical patterns, suggesting a probabilistic and dynamic process that is nonetheless compatible with apparent distinct milestones in development. We provide a new, systematic way of showing how developmental cascade theories could work in language development. Our findings and model also suggest insights into syntactic, semantic, and cognitive development.

Foggy connections, cloudy frontiers: On the (non-)adaptation of lexical structures

While research on possible adaptive processes in language history has recently centered mostly on phonological variables, here, I return the focus on the lexicon in two different ways. First, I take up the familiar theme of the responsiveness of language structure to the local conditions at different elevations of the earth's surface by exploring further the idea that language communities at high altitudes may tend not to distinguish lexically, as, e.g., English does, between "cloud" and "fog." Analyses of a global dataset of languages as well as in-depth study of the languages of the Central Andes are consistent in showing a wide spread of colexification of "cloud" and "fog" across elevations, whereas distinguishing languages tend more to be spoken at lower elevations. Statistically, there is global support for the idea that colexification is triggered by high elevation, but a closer look, in particular at the Andean dataset, paints a more nuanced picture. Concretely, it shows that in some language families, there are consistent preferences for either colexifying or distinguishing between "cloud" and "fog." In particular, the behavior of the large Quechuan family, which ranges across high- and low-elevation environments but still is consistently colexifying, shows no evidence for adaptive processes within language families. This result is open to various interpretations and explanations, for they suggest lineage-specific preferences for or against colexification that run counter to global trends. It is also at odds with the notions of "efficient communication" and "communicative need" as far as they relate to lexical categories and bars mechanistic or deterministic views on the processes in which the categories of languages are molded.

Zipfian Distributions in Child-Directed Speech

Across languages, word frequency and rank follow a power law relation, forming a distribution known as the Zipfian distribution. There is growing experimental evidence that this well-studied phenomenon may be beneficial for language learning. However, most investigations of word distributions in natural language have focused on adult-to-adult speech: Zipf's law has not been thoroughly evaluated in child-directed speech (CDS) across languages. If Zipfian distributions facilitate learning, they should also be found in CDS. At the same time, several unique properties of CDS may result in a less skewed distribution. Here, we examine the frequency distribution of words in CDS in three studies. We first show that CDS is Zipfian across 15 languages from seven language families. We then show that CDS is Zipfian from early on (six-months) and across development for five languages with sufficient longitudinal data. Finally, we show that the distribution holds across different parts of speech: Nouns, verbs, adjectives and prepositions follow a Zipfian distribution. Together, the results show that the input children hear is skewed in a particular way from early on, providing necessary (but not sufficient) support for the postulated learning advantage of such skew. They highlight the need to study skewed learning environments experimentally.

Over-reliance on English hinders cognitive science

English is the dominant language in the study of human cognition and behavior: the individuals studied by cognitive scientists, as well as most of the scientists themselves, are frequently English speakers. However, English differs from other languages in ways that have consequences for the whole of the cognitive sciences, reaching far beyond the study of language itself. Here, we review an emerging body of evidence that highlights how the particular characteristics of English and the linguistic habits of English speakers bias the field by both warping research programs (e.g., overemphasizing features and mechanisms present in English over others) and overgeneralizing observations from English speakers' behaviors, brains, and cognition to our entire species. We propose mitigating strategies that could help avoid some of these pitfalls.

Initial Development of an Automated Platform for Assessing Trainee Performance on Case Presentations

Background

Oral case presentation is a crucial skill of physicians and a key component of team-based care. However, consistent and objective assessment and feedback on presentations during training are infrequent.

Objective

To determine the potential value of applying natural language processing, computer software that extracts meaning from text, to transcripts of oral case presentations as a strategy to assess their quality automatically and objectively.

Methods

We transcribed a collection of simulated oral case presentations. The presentations were from eight critical care fellows and one critical care attending. They were instructed to review the medical charts of 11 real intensive care unit patient cases and to audio record themselves, presenting each case as if they were doing so on morning rounds. We then used natural language processing to convert the transcripts from human-readable text into machine-readable numbers. These numbers represent details of the presentation style and content. The distance between the numeric representation of two different transcripts negatively correlates with the similarity of those two transcripts. We ranked fellows on the basis of how similar their presentations were to the attending's presentations.

Results

The 99 presentations included 260 minutes of audio (mean length: 2.6 ± 1.24 min per case). On average, 23.88 ± 2.65 sentences were spoken, and each sentence had 14.10 ± 0.67 words, 3.62 ± 0.15 medical concepts, and 0.75 ± 0.09 medical adjectives. When ranking fellows on the basis of how similar their presentations were to the attending's presentation, we found a gap between the five fellows with the most similar presentations and the three fellows with the least similar presentations (average group similarity scores of 0.62 ± 0.01 and 0.53 ± 0.01, respectively). Rankings were sensitive to whether presentation style or content information were weighted more heavily when calculating transcript similarity.

Conclusion

Natural language processing enabled the ranking of case presentations on the basis of how similar they were to a reference presentation. Although additional work is needed to convert these rankings, and underlying similarity scores, into actionable feedback for trainees, these methods may support new tools for improving medical education.