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Abstract: This squib presents three new arguments that the matrix subject in English tough-constructions cannot reconstruct into the embedded gap. The first two arguments reexamine data in the literature purported to show such reconstruction. Upon closer scrutiny, we argue that these data in fact involve short reconstruction below a modal or generic operator in the matrix clause, and not genuine long reconstruction into the embedded gap. The third argument is that property positions, which independently require reconstruction, are unable to host tough-gaps. This ban on long reconstruction in English tough-constructions follows without further ado on a base-generation analysis.

Small, disc-shaped shell beads are recorded as mortuary offerings in many Neolithic and Bronze Age burials in Southeast Asia. Yet the provenance of these artefacts is often obscure, as production processes involve the removal of diagnostic morphological features, negating taxonomic classification. Here, the authors report on the combined isotopic and morphological analysis of a subset of shell beads from the site of Ban Non Wat in north-east Thailand. In addition to identifying freshwater sources for nearly all the beads, the results suggest the presence of multiple shell production centres - each with access to distinct aqueous environments - and widespread exchange in the Bronze Age.

Abstract: Large Language Models (LLMs) have been criticized for failing to connect linguistic meaning to the world—for failing to solve the “symbol grounding problem.” Multimodal Large Language Models (MLLMs) offer a potential solution to this challenge by combining linguistic representations and processing with other modalities. However, much is still unknown about exactly how and to what degree MLLMs integrate their distinct modalities—and whether the way they do so mirrors the mechanisms believed to underpin grounding in humans. In humans, it has been hypothesized that linguistic meaning is grounded through “embodied simulation,” the activation of sensorimotor and affective representations reflecting described experiences. Across four pre-registered studies, we adapt experimental techniques originally developed to investigate embodied simulation in human comprehenders to ask whether MLLMs are sensitive to sensorimotor features that are implied but not explicit in descriptions of an event. In Experiment 1, we find sensitivity to some features (color and shape) but not others (size, orientation, and volume). In Experiment 2, we identify likely bottlenecks to explain an MLLM’s lack of sensitivity. In Experiment 3, we find that despite sensitivity to implicit sensorimotor features, MLLMs cannot fully account for human behavior on the same task. Finally, in Experiment 4, we compare the psychometric predictive power of different MLLM architectures and find that ViLT, a single-stream architecture, is more predictive of human responses to one sensorimotor feature (shape) than CLIP, a dual-encoder architecture—despite being trained on orders of magnitude less data. These results reveal strengths and limitations in the ability of current MLLMs to integrate language with other modalities, and also shed light on the likely mechanisms underlying human language comprehension.

Abstract: Recent findings show adult New Zealanders who do not speak te reo Māori (the Māori language, the indigenous language of New Zealand) nonetheless have impressive implicit lexical and phonotactic knowledge of the language. These findings have been interpreted as showing that regular ambient exposure to a non-native language develops an implicit “proto-lexicon”, a memory store of lexical forms in that language, without any meaning. However, what is not known is the timeframe over which this knowledge is acquired. Does the knowledge stem exclusively from implicit learning during childhood, or does it continue to grow based on exposure during adulthood? To investigate this question, we directly compare non-Māori-speaking school-aged adolescents and adults in New Zealand and explore how age affects the degree of observed knowledge. Our results show that ambient exposure leads to implicit knowledge both in childhood and adulthood, and that continuing exposure throughout the lifespan leads to increased knowledge.

Supplemental material is available for this article.

This article provides three major contributions to the literature: we provide granular information on the development of student argumentative writing across secondary school; we replicate the MacArthur et al. model of Natural Language Processing (NLP) writing features that predict quality with a younger group of students; and we are able to examine the differences for students across language status. In our study, we sought to find the average levels of text length, cohesion, connectives, syntactic complexity, and word-level complexity in this sample across Grades 7-12 by sex, by English learner status, and for essays scoring above and below the median holistic score. Mean levels of variables by grade suggest a developmental progression with respect to text length, with the text length increasing with grade level, but the other variables in the model were fairly stable. Sex did not seem to affect the model in meaningful ways beyond the increased fluency of women writers. We saw text length and word level differences between initially designated and redesignated bilingual students compared to their English-only peers. Finally, we see that the model works better with our higher scoring essays and is less effective explaining the lower scoring essays.

Abstract: We address a growing debate about the extent to which large language models (LLMs) produce behavior consistent with Theory of Mind (ToM) in humans. We present EPITOME: a battery of six experiments that tap diverse ToM capacities, including belief attribution, emotional inference, and pragmatic reasoning. We elicit a performance baseline from human participants for each task. We use the dataset to ask whether distributional linguistic information learned by LLMs is sufficient to explain ToM in humans. We compare performance of five LLMs to a baseline of responses from human comprehenders. Results are mixed. LLMs display considerable sensitivity to mental states and match human performance in several tasks. Yet, they commit systematic errors in others, especially those requiring pragmatic reasoning on the basis of mental state information. Such uneven performance indicates that human-level ToM may require resources beyond distributional information.

BACKGROUND: Language in nonmedical data sets is known to transmit human-like biases when used in natural language processing (NLP) algorithms that can reinforce disparities. It is unclear if NLP algorithms of medical notes could lead to similar transmissions of biases. RESEARCH QUESTION: Can we identify implicit bias in clinical notes, and are biases stable across time and geography? STUDY DESIGN AND METHODS: To determine whether different racial and ethnic descriptors are similar contextually to stigmatizing language in ICU notes and whether these relationships are stable across time and geography, we identified notes on critically ill adults admitted to the University of California, San Francisco (UCSF), from 2012 through 2022 and to Beth Israel Deaconess Hospital (BIDMC) from 2001 through 2012. Because word meaning is derived largely from context, we trained unsupervised word-embedding algorithms to measure the similarity (cosine similarity) quantitatively of the context between a racial or ethnic descriptor (eg, African-American) and a stigmatizing target word (eg, nonco-operative) or group of words (violence, passivity, noncompliance, nonadherence). RESULTS: In UCSF notes, Black descriptors were less likely to be similar contextually to violent words compared with White descriptors. Contrastingly, in BIDMC notes, Black descriptors were more likely to be similar contextually to violent words compared with White descriptors. The UCSF data set also showed that Black descriptors were more similar contextually to passivity and noncompliance words compared with Latinx descriptors. INTERPRETATION: Implicit bias is identifiable in ICU notes. Racial and ethnic group descriptors carry different contextual relationships to stigmatizing words, depending on when and where notes were written. Because NLP models seem able to transmit implicit bias from training data, use of NLP algorithms in clinical prediction could reinforce disparities. Active debiasing strategies may be necessary to achieve algorithmic fairness when using language models in clinical research.

Abstract: A'ingae (or Cofán, ISO 639‐3: con) is an indigenous language isolate spoken in northeast Ecuador and southern Colombia. This paper presents the first comprehensive overview of the A'ingae phonology, including descriptions of (i) the language's phonemic inventory, (ii) phonotactics and a number of related phonological rules, (iii) nasality and nasal spreading, as well as (iv) stress, glottalisation, their morphophonology, and aspects of clause‐level prosody.

Relative to one's default (casual) speech, clear speech contains acoustic modifications that are often perceptually beneficial. Clear speech encompasses many different styles, yet most work only compares clear and casual speech as a binary. Furthermore, the term “clear speech” is often unclear − despite variation in elicitation instructions across studies (e.g., speak clearly, imagine an L2-listener or someone with hearing loss, etc.), the generic term “clear speech” is used when interpreting results, under the tacit assumption that clear speech is monolithic. The current study examined the acoustics and intelligibility of casual speech and two clear styles (hard-of-hearing-directed and non-native-directed speech). We find: (1) the clear styles are acoustically distinct (non-native-directed speech is slower with lower mean intensity and f0); (2) the clear styles are perceptually distinct (only hard-of-hearing-directed speech enhances intelligibility); (3) no differences in intelligibility benefits are observed between L1 and L2-listeners. These results underscore the importance of considering the intended interlocutor in speaking style elicitation, leading to a discussion about the issues that arise when reference to “clear speech” lacks clarity. It is suggested that to be more clear about clear speech, greater caution should be taken when interpreting results about speaking style variation.

Abstract: We investigated spelling errors in English and Spanish essays by Spanish-English dual language learners in Grades 1, 2, and 3 (N = 278; 51% female) enrolled in either English immersion or English-Spanish dual immersion programs. We examined what types of spelling errors students made, whether they made spelling errors that could be due to crosslinguistic influence, and whether errors were associated with instructional program, English learner status, and grade level. Compositions were transcribed and coded using the Systematic Analysis of Language Transcripts (SALT) software. Spelling errors were suggestive of crosslinguistic influence that was mostly unidirectional from one language to the other rather than bidirectional. Spelling errors were related to instructional program such that students in Spanish-English dual immersion made more English spelling errors in English compositions due to Spanish influence, and students in English immersion made more spelling errors in Spanish compositions due to English influence. Students in higher grades also made less English spelling errors in English compositions due to Spanish influence than students in lower grades. These findings suggest that dual language learners acquire spelling patterns in one language influenced by instruction and home language, which transfers to spelling in the other language.

What is the connection between the cultural evolution of a language and the rapid processing response to that language in the brains of individual learners? In an iterated communication study that was conducted previously, participants were asked to communicate temporal concepts such as "tomorrow," "day after," "year," and "past" using vertical movements recorded on a touch screen. Over time, participants developed simple artificial 'languages' that used space metaphorically to communicate in nuanced ways about time. Some conventions appeared rapidly and universally (e.g., using larger vertical movements to convey greater temporal durations). Other conventions required extensive social interaction and exhibited idiosyncratic variation (e.g., using vertical location to convey past or future). Here we investigate whether the brain's response during acquisition of such a language reflects the process by which the language's conventions originally evolved. We recorded participants' EEG as they learned one of these artificial space-time languages. Overall, the brain response to this artificial communication system was language-like, with, for instance, violations to the system's conventions eliciting an N400-like component. Over the course of learning, participants' brain responses developed in ways that paralleled the process by which the language had originally evolved, with early neural sensitivity to violations of a rapidly-evolving universal convention, and slowly developing neural sensitivity to an idiosyncratic convention that required slow social negotiation to emerge. This study opens up exciting avenues of future work to disentangle how neural biases influence learning and transmission in the emergence of structure in language.

All parts of Heraclitus’ cosmos are simultaneously living and dying. Its constituent stuffs (“biomasses”) cycle endlessly through physical changes in sweeping patterns (“biorhythms”) that are reflected in the dynamic rhythms of Heraclitus’ own thought and language. These natural processes are best examined at a more-than-human level that exceeds individuation, stable identity, rational comprehension, and linguistic capture. B62 (“mortals immortals”), one of Heraclitus’ most perplexing fragments, models these processes in a spectacular fashion: it describes the imbrication not only of humans and gods but of cosmic masses more generally, and its language mimics the natural relations that it names, or rather intimates through its grammatical and syntactical indeterminacy. The remaining fragments amplify the uncertainties and the exhilarations of Heraclitus’ worldview along the same lines. His approach to nature raises urgent questions about how human beings fit into the cosmos, not least by challenging our intuitive conceptions of life and death, our material makeup, and our entanglements with our natural surroundings. In doing so, he provides vital lessons for contemporary ecological awareness, and proves to be an unexpected ally.

The advent of patient access to complex medical information online has highlighted the need for simplification of biomedical text to improve patient understanding and engagement in taking ownership of their health. However, comprehension of biomedical text remains a difficult task due to the need for domain-specific expertise. We aimed to study the simplification of biomedical text via large language models (LLMs) commonly used for general natural language processing tasks involve text comprehension, summarization, generation, and prediction of new text from prompts. Specifically, we finetuned three variants of large language models to perform substitutions of complex words and word phrases in biomedical text with a related hypernym. The output of the text substitution process using LLMs was evaluated by comparing the pre- and post-substitution texts using four readability metrics and two measures of sentence complexity. A sample of 1,000 biomedical definitions in the National Library of Medicine's Unified Medical Language System (UMLS) was processed with three LLM approaches, and each showed an improvement in readability and sentence complexity after hypernym substitution. Readability scores were translated from a pre-processed collegiate reading level to a post-processed US high-school level. Comparison between the three LLMs showed that the GPT-J-6b approach had the best improvement in measures of sentence complexity. This study demonstrates the merit of hypernym substitution to improve readability of complex biomedical text for the public and highlights the use case for fine-tuning open-access large language models for biomedical natural language processing.

Abstract: The present study contributes to the empirical basis of grammaticalization theory by presenting a grammaticalization profile of Zapotec, a language family of Mesoamerica. The discussion centers around co-grammaticalization of lexemes and constructions, polygrammaticalization, interdependence between syntactic and prosodic conditioning of grammaticalization, and mutual feedback between grammaticalization and morphosyntactic typology.

PurposePast research shows that parentally responsive behavior toward the child positively influences language development in both neurotypical children and children with intellectual and developmental disabilities, including those with fragile X syndrome (FXS); however, most studies have focused exclusively on the mother-child relationship. The current study examined relationships between parent behavior (i.e., responsivity and behavior management) and child language performance in both mother-child and father-child interactions, as well as relationships between child characteristics and both parent behavior and child language.MethodParticipants were 23 families of young boys with FXS between 3 and 7 years of age. Mothers and fathers independently completed questionnaires assessing child characteristics and separately engaged in 12-min play-based interactions with their child via telehealth. One parent also completed a comprehensive interview assessing child adaptive behavior. Video recordings of the parent-child interactions were transcribed and coded for parent and child behavior, and measures of parent and child language were obtained from the transcripts.ResultsMothers and fathers used similar rates of responsive behaviors during parent-child interactions, and parental responsivity was positively associated with some aspects of child language performance (i.e., talkativeness and lexical diversity). Parental behavior, however, was not associated with syntactic complexity. Older children and children with higher levels of adaptive behavior had parents who used higher rates of responsive behaviors. Fathers used higher rates of behavior management strategies compared to mothers, and this type of parent behavior was not associated with child language.ConclusionOverall, this study provides evidence that interventions focused on increasing parental responsiveness would be beneficial for families of children with FXS and that these interventions should be delivered early given the association between responsivity and child age.Supplemental materialhttps://doi.org/10.23641/asha.25229939.

Bilingualism is thought to confer advantages in executive functioning, thereby contributing to cognitive reserve and a later age of dementia symptom onset. While the relation between bilingualism and age of onset has been explored in Alzheimer's dementia, there are few studies examining bilingualism as a contributor to cognitive reserve in frontotemporal dementia (FTD). In line with previous findings, we hypothesized that bilinguals with behavioral variant FTD would be older at symptom onset compared to monolinguals, but that no such effect would be found in patients with nonfluent/agrammatic variant primary progressive aphasia (PPA) or semantic variant PPA. Contrary to our hypothesis, we found no significant difference in age at symptom onset between monolingual and bilingual speakers within any of the FTD variants, and there were no notable differences on neuropsychological measures. Overall, our results do not support a protective effect of bilingualism in patients with FTD-spectrum disease in a U.S. based cohort.

In six experiments we explored how biphone probability and lexical neighborhood density influence listeners' categorization of vowels embedded in nonword sequences. We found independent effects of each. Listeners shifted categorization of a phonetic continuum to create a higher probability sequence, even when neighborhood density was controlled. Similarly, listeners shifted categorization to create a nonword from a denser neighborhood, even when biphone probability was controlled. Next, using a visual world eye-tracking task, we determined that biphone probability information is used rapidly by listeners in perception. In contrast, task complexity and irrelevant variability in the stimuli interfere with neighborhood density effects. These results support a model in which both biphone probability and neighborhood density independently affect word recognition, but only biphone probability effects are observed early in processing.

Abstract: The prevalence and strong capability of large language models (LLMs) present significant safety and ethical risks if exploited by malicious users. To prevent the potentially deceptive usage of LLMs, recent work has proposed algorithms to detect LLM-generated text and protect LLMs. In this paper, we investigate the robustness and reliability of these LLM detectors under adversarial attacks. We study two types of attack strategies: 1) replacing certain words in an LLM’s output with their synonyms given the context; 2) automatically searching for an instructional prompt to alter the writing style of the generation. In both strategies, we leverage an auxiliary LLM to generate the word replacements or the instructional prompt. Different from previous works, we consider a challenging setting where the auxiliary LLM can also be protected by a detector. Experiments reveal that our attacks effectively compromise the performance of all detectors in the study with plausible generations, underscoring the urgent need to improve the robustness of LLM-generated text detection systems. Code is available at https://github.com/shizhouxing/LLM-Detector-Robustness.

Children who receive cochlear implants develop spoken language on a protracted timescale. The home environment facilitates speech-language development, yet it is relatively unknown how the environment differs between children with cochlear implants and typical hearing. We matched eighteen preschoolers with implants (31-65 months) to two groups of children with typical hearing: by chronological age and hearing age. Each child completed a long-form, naturalistic audio recording of their home environment (appx. 16 hours/child; >730 hours of observation) to measure adult speech input, child vocal productivity, and caregiver-child interaction. Results showed that children with cochlear implants and typical hearing were exposed to and engaged in similar amounts of spoken language with caregivers. However, the home environment did not reflect developmental stages as closely for children with implants, or predict their speech outcomes as strongly. Home-based speech-language interventions should focus on the unique input-outcome relationships for this group of children with hearing loss.

Abstract: Language proficiency is a critically important factor in research on bilingualism, but researchers disagree on its measurement. Validated objective measures exist, but investigators often rely exclusively on subjective measures. We investigated if combining multiple self-report measures improves prediction of objective naming test scores in 36 English-dominant versus 32 Spanish-dominant older bilinguals (Experiment 1), and in 41 older Spanish–English bilinguals versus 41 proficiency-matched young bilinguals (Experiment 2). Self-rated proficiency was a powerful but sometimes inaccurate predictor and better predicted naming accuracy when combined with years of immersion, while percent use explained little or no unique variance. Spanish-dominant bilinguals rated themselves more strictly than English-dominant bilinguals at the same objectively measured proficiency level. Immersion affected young more than older bilinguals, and non-immersed (English-dominant) more than immersed (Spanish-dominant) bilinguals. Self-reported proficiency ratings can produce spurious results, but predictive power improves when combined with self-report questions that might be less affected by subjective judgements.

PurposeThe aims of this study were (a) to evaluate the convergent validity of the Language Use Inventory (LUI) with measures of autism spectrum disorder (ASD) symptoms, language, and social skills and (b) to assess discriminant validity of the LUI with measures of nonlanguage skills, including daily living skills and motor development.MethodThis study sample included participants from a longitudinal study (n = 239) of infant siblings with elevated familial likelihood of ASD and lower familial likelihood. Assessment measures completed at 36 months included the LUI, the Autism Diagnostic Observation Schedule-Second Edition (ADOS-2), the Mullen Scales of Early Learning, and the Vineland Adaptive Behavior Scales-Second Edition. Bivariate Pearson correlations were estimated between ADOS-2 comparison scores and four language and social skills measures. Additional correlations were estimated between LUI total scores and standard scores from nonlanguage measures. A series of Fisher's Z transformations were applied to evaluate whether bivariate correlations were significantly different.ResultsAll four language and social skill measures were moderately to strongly associated with each other and ASD symptom severity scores. The correlation between ADOS-2 comparison scores and LUI total scores was significantly stronger than ADOS-2 correlations with all other measures.ConclusionsOur findings provide support for the LUI as a feasible, pragmatic language-targeted instrument for inclusion in early developmental evaluations prompted by language concerns. Administration of the LUI may accelerate earlier referral for a comprehensive assessment of ASD symptoms. Given the high correlation with ADOS-2 scores, an LUI total score in a clinical range of concern may encourage a clinician to refer families for a full diagnostic evaluation of ASD.

The problem of characterizing voice quality has long caused debate and frustration. The richness of the available descriptive vocabulary is overwhelming, but the density and complexity of the information voices convey lead some to conclude that language can never adequately specify what we hear. Others argue that terminology lacks an empirical basis, so that language-based scales are inadequate a priori. Efforts to provide meaningful instrumental characterizations have also had limited success. Such measures may capture sound patterns but cannot at present explain what characteristics, intentions, or identity listeners attribute to the speaker based on those patterns. However, some terms continually reappear across studies. These terms align with acoustic dimensions accounting for variance across speakers and languages and correlate with size and arousal across species. This suggests that labels for quality rest on a bedrock of biology: We have evolved to perceive voices in terms of size/arousal, and these factors structure both voice acoustics and descriptive language. Such linkages could help integrate studies of signals and their meaning, producing a truly interdisciplinary approach to the study of voice.

Spoken language comprehension requires abstraction of linguistic information from speech, but the interaction between auditory and linguistic processing of speech remains poorly understood. Here, we investigate the nature of this abstraction using neural responses recorded intracranially while participants listened to conversational English speech. Capitalizing on multiple, language-specific patterns where phonological and acoustic information diverge, we demonstrate the causal efficacy of the phoneme as a unit of analysis and dissociate the unique contributions of phonemic and spectrographic information to neural responses. Quantitive higher-order response models also reveal that unique contributions of phonological information are carried in the covariance structure of the stimulus-response relationship. This suggests that linguistic abstraction is shaped by neurobiological mechanisms that involve integration across multiple spectro-temporal features and prior phonological information. These results link speech acoustics to phonology and morphosyntax, substantiating predictions about abstractness in linguistic theory and providing evidence for the acoustic features that support that abstraction.

Musical instrument training has been linked to improved academic and cognitive abilities in children, but it remains unclear why this occurs. Moreover, access to instrument training is not always feasible, thereby leaving less fortunate children without opportunity to benefit from such training. Although music-based video games may be more accessible to a broader population, research is lacking regarding their benefits on academic and cognitive performance. To address this gap, we assessed a custom-designed, digital rhythm training game as a proxy for instrument training to evaluate its ability to engender benefits in math and reading abilities. Furthermore, we tested for changes in core cognitive functions related to math and reading to inform how rhythm training may facilitate improved academic abilities. Classrooms of 8-9 year old children were randomized to receive either 6 weeks of rhythm training (N = 32) or classroom instruction as usual (control; N = 21). Compared to the control group, results showed that rhythm training improved reading, but not math, fluency. Assessments of cognition showed that rhythm training also led to improved rhythmic timing and language-based executive function (Stroop task), but not sustained attention, inhibitory control, or working memory. Interestingly, only the improvements in rhythmic timing correlated with improvements in reading ability. Together, these results provide novel evidence that a digital platform may serve as a proxy for musical instrument training to facilitate reading fluency in children, and that such reading improvements are related to enhanced rhythmic timing ability and not other cognitive functions associated with reading performance. RESEARCH HIGHLIGHTS: Digital rhythm training in the classroom can improve reading fluency in 8-9 year old children Improvements in reading fluency were positively correlated with enhanced rhythmic timing ability Alterations in reading fluency were not predicted by changes in other executive functions that support reading A digital platform may be a convenient and cost-effective means to provide musical rhythm training, which in turn, can facilitate academic skills.

The process by which infants learn verbs through daily social interactions is not well-understood. This study investigated caregivers' use of verbs, which have highly abstract meanings, during unscripted toy-play. We examined how verbs co-occurred with distributional and embodied factors including pronouns, caregivers' manual actions, and infants' locomotion, gaze, and object-touching. Object-action verbs were used significantly more often during caregiver-infant joint attention interactions. Movement and cognition verbs showed distinct co-occurrences with different contexts. Cognition and volition verbs were differentiated by pronouns. These findings provide evidence for how verb acquisition may be supported by the distributional and embodied contexts in caregiver-infant interactions.

Abstract: Recent work has claimed that (non-tonal) phonological patterns are subregular (Heinz 2011a,b, 2018; Heinz and Idsardi 2013), occupying a delimited proper subregion of the regular functions—the weakly deterministic (WD) functions (Heinz and Lai 2013; Jardine 2016). Whether or not it is correct (McCollum et al. 2020a), this claim can only be properly assessed given a complete and accurate definition of WD functions. We propose such a definition in this article, patching unintended holes in Heinz and Lai’s (2013) original definition that we argue have led to the incorrect classification of some phonological patterns as WD. We start from the observation that WD patterns share a property that we call unbounded semiambience, modeled after the analogous observation by Jardine (2016) about non-deterministic (ND) patterns and their unbounded circumambience. Both ND and WD functions can be broken down into compositions of deterministic (subsequential) functions (Elgot and Mezei 1965; Heinz and Lai 2013) that read an input string from opposite directions; we show that WD functions are those for which these deterministic composands do not interact in a way that is familiar from the theoretical phonology literature. To underscore how this concept of interaction neatly separates the WD class of functions from the strictly more expressive ND class, we provide analyses of the vowel harmony patterns of two Eastern Nilotic languages, Maasai and Turkana, using bimachines, an automaton type that represents unbounded bidirectional dependencies explicitly. These analyses make clear that there is interaction between deterministic composands when (and only when) the output of a given input element of a string is simultaneously dependent on information from both the left and the right: ND functions are those that involve interaction, while WD functions are those that do not.

Abstract: The intervocalic position favors voicing in stops. Yet, some languages have been reported to feature the opposite (unnatural) process of intervocalic devoicing. This paper investigates two such case studies. Pre-Berawan intervocalic *b and *g have developed into Berawan k. Pre-Kiput intervocalic *g, *ɟʝ, and *v have developed into Kiput k, cç, and f, respectively. To account for the data, we invoke Beguš’s (2018, 2019) blurring process model of sound change. The model proposes that unnatural phonology derives from a sequence of at least three phonetically motivated sound changes. We argue that the steps involved in intervocalic devoicing are (i) the intervocalic fricativization of voiced stops, (ii) devoicing of fricatives, and (iii) the occlusion of devoiced fricatives. Each of the steps is independently attested and motivated. We demonstrate that our blurring process proposal explains aspects of the historical development unaccounted for by previous approaches, and present new evidence suggesting that a single sound change could not have operated in the prehistory of Berawan. Thus, we maintain the conservative position that unnatural diachronic developments arise from sequences of natural and phonetically grounded sound changes.

Abstract: In some cultures, merely exerting effort is considered virtuous, even when the effort is inefficient. Our study examines how this moral attitude towards effort (relative to efficiency) has evolved historically across two distinct sociopolitical and linguistic contexts: the People’s Republic of China and the United States, using natural language processing techniques. Specifically, two formal political corpora were used—the People’s Daily (1950–2021) and the Congressional speeches for the U.S. (1873–2011). We developed dictionaries for each concept based on pre-trained word embedding models in both languages. Moral attitudes towards effort and efficiency were calculated on a year-by-year basis as the cosine similarity between the dictionaries of these concepts and an existing dictionary of morality. We benchmarked the fluctuations of moral attitude towards inefficient effort against critical historical events in the two countries. Additional time series analysis and Granger tests revealed the association and potential directionality between the evolution of moral attitude towards inefficient effort and critical socio-cultural variables such as collectivism and cultural looseness. Our research sheds light on the historical and socio-cultural roots of moralization of effort and has implications for historical psychology research on moral attitudes.

The rapid advances in Generative AI tools have produced both excitement and worry about how AI will impact academic writing. However, little is known about what norms are emerging around AI use in manuscript preparation or how these norms might be enforced. We address both gaps in the literature by conducting a survey of 271 academics about whether it is necessary to report ChatGPT use in manuscript preparation and by running GPT-modified abstracts from 2,716 published papers through a leading AI detection software to see if these detectors can detect different AI uses in manuscript preparation. We find that most academics do not think that using ChatGPT to fix grammar needs to be reported, but detection software did not always draw this distinction, as abstracts for which GPT was used to fix grammar were often flagged as having a high chance of being written by AI. We also find disagreements among academics on whether more substantial use of ChatGPT to rewrite text needs to be reported, and these differences were related to perceptions of ethics, academic role, and English language background. Finally, we found little difference in their perceptions about reporting ChatGPT and research assistant help, but significant differences in reporting perceptions between these sources of assistance and paid proofreading and other AI assistant tools (Grammarly and Word). Our results suggest that there might be challenges in getting authors to report AI use in manuscript preparation because (i) there is not uniform agreement about what uses of AI should be reported and (ii) journals might have trouble enforcing nuanced reporting requirements using AI detection tools.

This issue of Himalayan Linguistics marks twenty years for the journal. We reflect on the early history of Himalayan Linguistics, its contribution to the field, and the future of the journal.

Abstract: To what extent can statistical language knowledge account for the effects of world knowledge in language comprehension? We address this question by focusing on a core aspect of language understanding: pronoun resolution. While existing studies suggest that comprehenders use world knowledge to resolve pronouns, the distributional hypothesis and its operationalization in large language models (LLMs) provide an alternative account of how purely linguistic information could drive apparent world knowledge effects. We addressed these confounds in two experiments. In Experiment 1, we found a strong effect of world knowledge plausibility (measured using a norming study) on responses to comprehension questions that probed pronoun interpretation. In experiment 2, participants were slower to read continuations that contradicted world knowledge-consistent interpretations of a pronoun, implying that comprehenders deploy world knowledge spontaneously. Both effects persisted when controlling for the predictions of GPT-3, an LLM, suggesting that pronoun interpretation is at least partly driven by knowledge about the world and not the word. We propose two potential mechanisms by which knowledge-driven pronoun resolution occurs, based on validation- and expectation-driven discourse processes. The results suggest that while distributional information may capture some aspects of world knowledge, human comprehenders likely draw on other sources unavailable to LLMs.

Aims and objectives: The existing literature indicates that shared book reading is associated with benefits in children’s home language development. Parents play a significant role in shaping children’s language outcomes. The purpose of this study was to investigate the relations among the quality of parents’ shared book reading, children’s language output, receptive vocabulary, and expressive vocabulary outcomes in the home language of dual language learners (DLLs) to inform book reading practices that can support DLLs’ early home language development. Methodology: 36 Mexican American (43–67 months) and 31 Chinese American (38–70 months) DLLs and their mothers, who were home language dominant, were recruited from Head Start programs, which are federally funded programs that provide early childhood education to low-income children, in Northern California. Data and analysis: Utterances produced by the parents during parent–child shared book reading were coded for cognitive demand levels. DLLs’ home language expressive vocabulary and receptive vocabulary and information about parents’ demographics and parent–child shared reading frequency were collected. Correlations and hierarchical regression analyses were computed. Findings/conclusions: The findings demonstrated possible cultural differences in mothers’ book reading quality regarding cognitive demand. Although maternal statements and questions were not significantly associated with DLLs’ home language receptive and expressive vocabulary for both groups, asking yes/no, referential, and inferential questions were more likely to evoke more language output from DLLs. Originality: This study extends the literature on home language development of low-income DLLs during parent–child shared reading, as only a few studies have investigated the significance of shared reading in the home language. Significance/implications: The findings of this study yield important implications for parents’ shared reading practices with low-income DLLs. Using all levels of cognitively demanding speech and encouraging DLLs to talk during shared reading may benefit their home language development.

Abstract: This paper argues that not all reconstruction effects can be reduced to a syntactic mechanism that selectively interprets copies at LF. The argument is based on the novel observation that some but not all reconstruction effects induce Condition C connectivity in Hindi-Urdu. We contend that Hindi-Urdu requires the hybrid approach to reconstruction developed on independent grounds by Lechner (1998, 2013, 2019), where both copy neglect (a syntactic mechanism) and higher-type traces (a semantic mechanism) are available as independent interpretive mechanisms. We show that the interaction of these two modes of reconstruction derives the intricate reconstruction facts in Hindi-Urdu.

Preminger (to appear) claims that an AGREE-based theory of case assignment undergenerates because it cannot handle attested dependent-case patterns. This paper argues that dependent-case assignment can in fact be modelled using the operation AGREE, building on independently motivated assumptions. Therefore, an AGREE-based theory of case assignment does not undergenerate.

Abstract: The dative alternation has been extensively studied in the world’s languages, and the meanings of the verbs participating in the alternation have been shown to play a key role in determining its argument realization options. The present paper presents a multiple distinctive collexeme analysis approach to the dative alternation in Mandarin Chinese, which involves a choice of one of five functionally similar alternants, and it does so by also discussing several ways to improve how this has been done statistically in most previous analyses. Linguistically, we identify the core semantic differences of the five constructions based on which verbs statistically prefer to occur in which pattern, focusing on semantic potential and direction of transfer. Methodologically, this study contributes to the slowly growing body of studies that use collexeme strengths that are not only less related to frequency than the traditional methods (i.e., association is measured in a less diluted way) and that are directional (i.e., we can focus on one direction of association from the verb to the construction).

Compositionality, or the ability to build complex representations from discrete elements, is an essential ingredient of human intelligence. Compositionality enables people to think productively, learn fast from limited experience, and generalize knowledge to new contexts without re-learning from scratch. It is also essential in information processing systems to efficiently represent structured data and has seen application in compression and symbolic Artificial Intelligence (AI). Historically, the notion of compositionality played a central role in linguistic theory and philosophy of mind. More recently, it is attracting a surge of interest throughout the domains of cognitive science. Compositional processes are leveraged for elucidating the nature of mental representations in cognition (Dehaene et al., 2022), understanding the functional organisation of the brain (Agrawal et al., 2019), or building Artificial Intelligence systems that are robust to changes in the environment (Hupkes et al., 2020).

We investigated the impact of teachers' multimodal cues on L2 word learning in naturalistic teaching. 169 university students randomly watched 12 of 54 clips of English vocabulary instructions and took subsequent word recognition and learning tests. The learning outcomes were analysed as a function of teachers' prosodic, linguistic and gestural input during the instruction of each vocabulary while controlling for students' characteristics and varying teachers' influences. Results showed that a shorter mean length of utterances, fewer L2 English words, and more questions for students and “phrase” teaching predicted better learning outcomes. Furthermore, students learning improved with teachers' slower speaking rate but fewer pauses and more iconic gestures. These results were robust even after controlling for other significant factors such as students' English proficiency, working memory, degree of liking of teachers and different teachers. Overall, multimodal cues enhance L2 vocabulary learning, with implications for educators, linguists, and cognitive scientists.

In-context learning refers to the ability of a neural network to learn from information presented in its context. While traditional learning in neural networks requires adjusting network weights for every new task, in-context learning operates purely by updating internal activations without needing any updates to network weights. The emergence of this ability in large language models has led to a paradigm shift in machine learning and has forced researchers to reconceptualize how they think about learning in neural networks. Looking beyond language models, we can find in-context learning in many computational models relevant to cognitive science, including those that emerge from meta-learning.

To communicate is to move. There is no way around that. Ifwe pick up comprehensive handbooks or introductory textsin movement science (Hong and Bartlett (2008)) we seethat there is very rich knowledge and tractable mathematicalmodels about different aspects of movements. Yet, we findno chapter on communicative movements. While the fieldof speech motor control is a developed area on its own(Parrell and Lammert (2019)), there is no movement scienceof communication proper, which would include whole-body-,hand-gestural-, signed-, and inter-bodily actions.

Events are a fundamental part of human experience. Research on event cognition is rapidly developing and is revealing central aspects of how humans perceive, conceptualize, communicate about, and remember events. This symposium offers an interdisciplinary look at recent advances in the study of event cognition. The symposium brings together cognitive scientists from across continents, who are experts on the subject. The symposium contributors come from a variety of backgrounds and disciplines in developmental psychology, cognitive psychology, neuro-computational psychology, and linguistics. They combine a variety of innovative and integrative approaches and methodologies and study diverse populations across the lifespan and across languages. The overall goal of this symposium is to foster an interdisciplinary conversation on different aspects of event cognition.

Goals are a central pillar of everyday mental activity. From finding your way home to solving a puzzle and ordering food delivery, much of human action and cognition is goal-directed. Perhaps unsurprisingly, theories of goals are a central focus in the psychology of motivation (Elliott & Dweck, 1988), in social and personality psychology (Fishbach & Ferguson, 2007), as well as research aimed at understanding factors contributing to task achievement in educational and industrial settings (Ames & Ames, 1984; Locke & Latham, 2002). In this symposium, we highlight recent work emphasizing a goal-centric outlook on learning, exploration, and communication.

We examine the relation between event segmentation in language and cognition in the domain of motion events, focusing on Turkish, a verb-framed language that segments motion paths in separate linguistic units (verb clauses). We compare motion events that have a path change to those that did not have a path change. In the linguistic task, participants were more likely to use multiple verb phrases when describing events that had a path change compared to those that did not have a path change. In the non-linguistic Dwell Time task, participants viewed self-paced slideshows of still images sampled from the motion event videos in the linguistic task. Dwell times for slides corresponding to path changes were not significantly longer than those for temporally similar slides in the events without a path change. These findings suggest that event units in language may not have strong and stable influences on event segmentation in cognition.

Computational psycholinguistics has traditionally employed a complexity metric called Node Count, which counts the number of syntactic nodes representing syntactic structures and predicts processing costs in human sentence processing. However, Node Count does not dissociate distinct syntactic operations deriving those syntactic structures, so that how much processing cost each syntactic operation induces remains to be investigated. In this paper, we introduce a novel complexity metric dubbed Composition Count, which counts the number of syntactic operations deriving syntactic structures, allowing us to understand the computational system of human sentence processing from the derivational, not representational, perspective. Specifically, employing Combinatory Categorial Grammar (CCG) which is equipped with multiple syntactic operations and thus suitable for the purpose here, we investigate (i) how much distinct syntactic operations of CCG contribute to predicting human reading times, and (ii) whether the same holds across languages. The results demonstrate that distinct syntactic operations of CCG have independent and cross-linguistic contributions to predicting human reading times, while Node Count turns out not to be robust cross-linguistically. In conclusion, these results strongly suggest the importance of Composition Count to dissociate distinct syntactic operations, not whole syntactic representations, and understand the computational system of human sentence processing.

Understanding spoken words requires listeners to integrate large amounts of linguistic information over time. There has been considerable debate about how semantic context preceding or following a target word affects its recognition, with preceding semantic context often viewed as a constraint on possible future words, and following semantic context as a mechanism for disambiguating previous ambiguous input. Surprisingly, no studies have directly compared whether the timing of semantic context influences spoken word recognition. The current study manipulates the acoustic-perceptual features of a target word, a semantic cue elsewhere in the sentence biasing toward one interpretation, and the location of the semantic context. We find that the two cues are additively integrated in participants' word identification responses, and that semantic context affects categorization the same regardless of where it appears relative to the target word. This suggests that listeners can optimally integrate acoustic-perceptual and semantic information across time.