Alternative Solutions to a Language Design Problem: The Role of Adjectives and Gender Marking in Efficient Communication

Grammatical Gender Disambiguates Syntactically Similar Nouns

Recent research into grammatical gender from the perspective of information theory has shown how seemingly arbitrary gender systems can ease processing demands by guiding lexical prediction. When the gender of a noun is revealed in a preceding element, the list of possible candidates is reduced to the nouns assigned to that gender. This strategy can be particularly effective if it eliminates words that are likely to compete for activation against the intended word. We propose syntax as the crucial context within which words must be disambiguated, hypothesizing that syntactically similar words should be less likely to share a gender cross-linguistically. We draw on recent work on syntactic information in the lexicon to define the syntactic distribution of a word as a probability vector of its participation in various dependency relations, and we extract such relations for 32 languages from the Universal Dependencies Treebanks. Correlational and mixed-effects regression analyses reveal that syntactically similar nouns are less likely to share a gender, the opposite pattern that is found for semantically and orthographically similar words. We interpret this finding as a design feature of language, and this study adds to a growing body of research attesting to the ways in which functional pressures on learning, memory, production, and perception shape the lexicon in different ways.

Languages are efficient, but for whom?

Human languages evolve to make communication more efficient. But efficiency creates trade-offs: what is efficient for speakers is not always efficient for comprehenders. How do languages balance these competing pressures? We focus on Zipf's meaning-frequency law, the observation that frequent wordforms have more meanings. On the one hand, this law could reflect a speaker-oriented pressure to reuse frequent wordforms. Yet human languages still maintain thousands of distinct wordforms, suggesting a countervailing, comprehender-oriented pressure. What balance of these pressures produces Zipf's meaning-frequency law? Using a neutral baseline, we find that frequent wordforms in real lexica have fewer homophones than predicted by their phonotactic structure: real lexica favor a comprehender-oriented pressure to reduce the cost of frequent disambiguation. These results help clarify the evolutionary drive for efficiency: human languages are subject to competing pressures for efficient communication, the relative magnitudes of which reveal how individual-level cognitive constraints shape languages over time.

How children learn to communicate discriminatively

How do children learn to communicate, and what do they learn? Traditionally, most theories have taken an associative, compositional approach to these questions, supposing children acquire an inventory of form-meaning associations, and procedures for composing / decomposing them; into / from messages in production and comprehension. This paper presents an alternative account of human communication and its acquisition based on the systematic, discriminative approach embodied in psychological and computational models of learning, and formally described by communication theory. It describes how discriminative learning theory offers an alternative perspective on the way that systems of semantic cues are conditioned onto communicative codes, while information theory provides a very different view of the nature of the codes themselves. It shows how the distributional properties of languages satisfy the communicative requirements described in information theory, enabling language learners to align their expectations despite the vastly different levels of experience among language users, and to master communication systems far more abstract than linguistic intuitions traditionally assume. Topics reviewed include morphological development, the acquisition of verb argument structures, and the functions of linguistic systems that have proven to be stumbling blocks for compositional theories: grammatical gender and personal names.

Prenominal adjective order is such a fat big deal because adjectives are ordered by likely need

When multiple adjectives precede a noun in English, they are often ordered in a way that is implicitly understood by all fluent speakers of the language. Adjective order might be described as a big fat deal, but to describe it as a fat big deal betrays a lack of knowledge of English. Sweet (A New English Grammar: Part II, 1898/1955) proposed two related semantic principles to explain the phenomenon: definiteness of denotation (adjectives that denote a property that is most independent of the modified noun must be placed furthest from that noun) and closeness of adjective/noun in meaning (adjectives that denote properties essential to or inherent in the modified noun are placed closer to the noun). These observational descriptions of the phenomenon have received experimental support (Martin, Journal of Verbal Learning and Verbal Behavior, 8(6), 697-704, 1969). However, the issue of why Sweet's rules are true has not yet been solved. I propose, operationalize, test, and find strong support for a simple theory: that prenominal adjective order reflects likely need, the a priori probability that a particular adjective will be needed.

Starting Big: The Effect of Unit Size on Language Learning in Children and Adults

Multiword units play an important role in language learning and use. It was proposed that learning from such units can facilitate mastery of certain grammatical relations, and that children and adults differ in their use of multiword units during learning, contributing to their varying language-learning trajectories. Accordingly, adults learn gender agreement better when encouraged to learn from multiword units. Previous work has not examined two core predictions of this proposal: (1) that children also benefit from initial exposure to multiword units, and (2) that their learning patterns reflect a greater reliance on multiword units compared to adults. We test both predictions using an artificial-language. As predicted, both children and adults benefit from early exposure to multiword units. In addition, when exposed to unsegmented input - adults show better learning of nouns compared to article-noun pairings, but children do not, a pattern consistent with adults' predicted tendency to focus less on multiword units.

Quantifying the speech-gesture relation with massive multimodal datasets: Informativity in time expressions

The development of large-scale corpora has led to a quantum leap in our understanding of speech in recent years. By contrast, the analysis of massive datasets has so far had a limited impact on the study of gesture and other visual communicative behaviors. We utilized the UCLA-Red Hen Lab multi-billion-word repository of video recordings, all of them showing communicative behavior that was not elicited in a lab, to quantify speech-gesture co-occurrence frequency for a subset of linguistic expressions in American English. First, we objectively establish a systematic relationship in the high degree of co-occurrence between gesture and speech in our subset of expressions, which consists of temporal phrases. Second, we show that there is a systematic alignment between the informativity of co-speech gestures and that of the verbal expressions with which they co-occur. By exposing deep, systematic relations between the modalities of gesture and speech, our results pave the way for the data-driven integration of multimodal behavior into our understanding of human communication.

How the Probabilistic Structure of Grammatical Context Shapes Speech

Does systematic covariation in the usage patterns of forms shape the sublexical variance observed in conversational speech? We address this question in terms of a recently proposed discriminative theory of human communication that argues that the distribution of events in communicative contexts should maintain mutual predictability between language users, present evidence that the distributions of words in the empirical contexts in which they are learned and used are geometric, and thus support this. Here, we extend this analysis to a corpus of conversational English, showing that the distribution of grammatical regularities and the sub-distributions of tokens discriminated by them are also geometric. Further analyses reveal a range of structural differences in the distribution of types in parts of speech categories that further support the suggestion that linguistic distributions (and codes) are subcategorized by context at multiple levels of abstraction. Finally, a series of analyses of the variation in spoken language reveals that quantifiable differences in the structure of lexical subcategories appears in turn to systematically shape sublexical variation in speech signal.

How Efficiency Shapes Human Language

Cognitive science applies diverse tools and perspectives to study human language. Recently, an exciting body of work has examined linguistic phenomena through the lens of efficiency in usage: what otherwise puzzling features of language find explanation in formal accounts of how language might be optimized for communication and learning? Here, we review studies that deploy formal tools from probability and information theory to understand how and why language works the way that it does, focusing on phenomena ranging from the lexicon through syntax. These studies show how a pervasive pressure for efficiency guides the forms of natural language and indicate that a rich future for language research lies in connecting linguistics to cognitive psychology and mathematical theories of communication and inference.

Information and learning in processing adjective inflection

We investigated the processing of inflected Serbian adjective forms to bring together quantitative linguistic measures from two frameworks - information theory and discrimination learning. From each framework we derived several quantitative descriptions of an inflectional morphological system and fitted two separate regression models to the processing latencies that were elicited by inflected adjectival forms presented in a visual lexical decision task. The model, which was based on lexical distributional and information theory revealed a dynamic interplay of information. The information was sensitive to syntagmatic and paradigmatic dimensions of variation; the paradigmatic information (formalized as respective relative entropies) was also modulated by lemma frequency. The discrimination learning based model revealed an equally complex pattern, involving several learning-based variables. The two models revealed strikingly similar patterns of results, as confirmed by the very high proportion of shared variance in model predictions (85.83%). Our findings add to the body of research demonstrating that complex morphological phenomena can arise as a consequence of the basic principles of discrimination learning. Learning discriminatively about inflectional paradigms and classes, and about their contextual or syntagmatic embedding, sheds light on human language-processing efficiency and on the fascinating complexity of naturally emerged language systems.