The basic reproductive ratio of a word, the maximum size of a lexicon

Language is about words and rules. While there is some discussion to what extent rules are learned or innate, it is clear that words have to be learned. Here I construct a mathematical framework for the population dynamics of language evolution with particular emphasis on how words are propagated over generations. I define the basic reproductive ratio of word, R, and show that R > 1 is required for words to be maintained in the lexicon of a language. Assuming that the frequency distribution of words follow Zipf's law, an upper limit is obtained for the number of words in a language that relies exclusively on oral transmission.     

The Effect of Sign Language Structure on Complex Word Reading in Chinese Deaf Adolescents

The present study was carried out to investigate whether sign language structure plays a role in the processing of complex words (i.e., derivational and compound words), in particular, the delay of complex word reading in deaf adolescents. Chinese deaf adolescents were found to respond faster to derivational words than to compound words for one-sign-structure words, but showed comparable performance for two-sign-structure words. For both derivational and compound words, response latencies to one-sign-structure words were shorter than to two-sign-structure words. These results provide strong evidence that the structure of sign language affects written word processing in Chinese. Additionally, differences between derivational and compound words in the one-sign-structure condition indicate that Chinese deaf adolescents acquire print morphological awareness. The results also showed that delayed word reading was found in derivational words with two signs (DW-2), compound words with one sign (CW-1), and compound words with two signs (CW-2), but not in derivational words with one sign (DW-1), with the delay being maximum in DW-2, medium in CW-2, and minimum in CW-1, suggesting that the structure of sign language has an impact on the delayed processing of Chinese written words in deaf adolescents. These results provide insight into the mechanisms about how sign language structure affects written word processing and its delayed processing relative to their hearing peers of the same age.     

Incidental Acquisition of Foreign Language Vocabulary through Brief Multi-Modal Exposure

First language acquisition requires relatively little effort compared to foreign language acquisition and happens more naturally through informal learning. Informal exposure can also benefit foreign language learning, although evidence for this has been limited to speech perception and production. An important question is whether informal exposure to spoken foreign language also leads to vocabulary learning through the creation of form-meaning links. Here we tested the impact of exposure to foreign language words presented with pictures in an incidental learning phase on subsequent explicit foreign language learning. In the explicit learning phase, we asked adults to learn translation equivalents of foreign language words, some of which had appeared in the incidental learning phase. Results revealed rapid learning of the foreign language words in the incidental learning phase showing that informal exposure to multi-modal foreign language leads to foreign language vocabulary acquisition. The creation of form-meaning links during the incidental learning phase is discussed.     

双语语言转换中存在语音效应和语言转换代价吗?——来自ERP的证据

目的:考察双语语音转换中是否存在语音效应。方法:选取19名汉英双语在校英语专业研究生为被试,应用ERP技术和出声的图片命名任务考察双语语言转换中的语音效应。结果:(1)语音效应方面,封闭语境条件下,英语的平均波幅显著大于汉语的平均波幅,语言类型差异显著;音译词和非音译词的平均波幅差异不显著;混合语境条件下,音译词的平均波幅均小于非音译词的平均波幅;非转换语境的平均波幅均大于转换语境的平均波幅,转换语境比非转换语境的词汇更容易被激活。(2)转换代价方面,混合语境条件下,音译词和非音译词之间的转换代价差异不显著,汉语和英语间的转换代价差异显著,熟练语言的转换代价大于非熟练语言的转换代价。结论:(1)封闭语境条件下不产生语音效应,混合语境条件下产生语音效应。(2)熟练语言的转换代价大于非熟练语言的转换代价。(3)语音效应与语境有关,语言转换代价与语言熟练程度有关。     

Capacity of making choices in the brain and its quantitative evaluation: an application to comprehension of incomplete sentences and semantic commitments.

The natural language processor in the brain generates information when it disambiguates words while reading a text in which information generation refers to making semantic commitments. Contextual facilitation of disambiguation of words appearing in the perturbed text that is derived from the unperturbed and natural one by deleting words randomly, lets the language processor revise the previous semantic commitments continuously. As the frequency of revising the previous semantic commitments increases, the amount of information generated by the language processor also increases. Revising previous semantic commitments in a continuous fashion is the functional property intrinsic to the language processor in the brain.     

Language as an evolving word web.

Human language may be described as a complex network of linked words. In such a treatment, each distinct word in language is a vertex of this web, and interacting words in sentences are connected by edges. The empirical distribution of the number of connections of words in this network is of a peculiar form that includes two pronounced power-law regions. Here we propose a theory of the evolution of language, which treats language as a self-organizing network of interacting words. In the framework of this concept, we completely describe the observed word web structure without any fitting. We show that the two regimes in the distribution naturally emerge from the evolutionary dynamics of the word web. It follows from our theory that the size of the core part of language, the 'kernel lexicon', does not vary as language evolves.     

Different neurophysiological mechanisms underlying word and rule extraction from speech

The initial process of identifying words from spoken language and the detection of more subtle regularities underlying their structure are mandatory processes for language acquisition. Little is known about the cognitive mechanisms that allow us to extract these two types of information and their specific time-course of acquisition following initial contact with a new language. We report time-related electrophysiological changes that occurred while participants learned an artificial language. These changes strongly correlated with the discovery of the structural rules embedded in the words. These changes were clearly different from those related to word learning and occurred during the first minutes of exposition. There is a functional distinction in the nature of the electrophysiological signals during acquisition: an increase in negativity (N400) in the central electrodes is related to word-learning and development of a frontal positivity (P2) is related to rule-learning. In addition, the results of an online implicit and a post-learning test indicate that, once the rules of the language have been acquired, new words following the rule are processed as words of the language. By contrast, new words violating the rule induce syntax-related electrophysiological responses when inserted online in the stream (an early frontal negativity followed by a late posterior positivity) and clear lexical effects when presented in isolation (N400 modulation). The present study provides direct evidence suggesting that the mechanisms to extract words and structural dependencies from continuous speech are functionally segregated. When these mechanisms are engaged, the electrophysiological marker associated with rule-learning appears very quickly, during the earliest phases of exposition to a new language.     

Connectivity,Not Frequency,Determines the Fate of a Morpheme

Morphemes are the smallest meaningful parts of words and therefore represent a natural unit to study the evolution of words. To analyze the influence of language change on morphemes, we performed a large scale analysis of German and English vocabulary covering the last 200 years. Using a network approach from bioinformatics, we examined the historical dynamics of morphemes, the fixation of new morphemes and the emergence of words containing existing morphemes. We found that these processes are driven mainly by the number of different direct neighbors of a morpheme in words (connectivity, an equivalent to family size or type frequency) and not its frequency of usage (equivalent to token frequency). This contrasts words, whose survival is determined by their frequency of usage. We therefore identified features of morphemes which are not dictated by the statistical properties of words. As morphemes are also relevant for the mental representation of words, this result might enable establishing a link between an individual’s perception of language and historical language change.     

How do we use language? Shared patterns in the frequency of word use across 17 world languages

We present data from 17 languages on the frequency with which a common set of words is used in everyday language. The languages are drawn from six language families representing 65 per cent of the world's 7000 languages. Our data were collected from linguistic corpora that record frequencies of use for the 200 meanings in the widely used Swadesh fundamental vocabulary. Our interest is to assess evidence for shared patterns of language use around the world, and for the relationship of language use to rates of lexical replacement, defined as the replacement of a word by a new unrelated or non-cognate word. Frequencies of use for words in the Swadesh list range from just a few per million words of speech to 191 000 or more. The average inter-correlation among languages in the frequency of use across the 200 words is 0.73 (p < 0.0001). The first principal component of these data accounts for 70 per cent of the variance in frequency of use. Elsewhere, we have shown that frequently used words in the Indo-European languages tend to be more conserved, and that this relationship holds separately for different parts of speech. A regression model combining the principal factor loadings derived from the worldwide sample along with their part of speech predicts 46 per cent of the variance in the rates of lexical replacement in the Indo-European languages. This suggests that Indo-European lexical replacement rates might be broadly representative of worldwide rates of change. Evidence for this speculation comes from using the same factor loadings and part-of-speech categories to predict a word's position in a list of 110 words ranked from slowest to most rapidly evolving among 14 of the world's language families. This regression model accounts for 30 per cent of the variance. Our results point to a remarkable regularity in the way that human speakers use language, and hint that the words for a shared set of meanings have been slowly evolving and others more rapidly evolving throughout human history.     

Learning and Long-Term Retention of Large-Scale Artificial Languages

Recovering discrete words from continuous speech is one of the first challenges facing language learners. Infants and adults can make use of the statistical structure of utterances to learn the forms of words from unsegmented input, suggesting that this ability may be useful for bootstrapping language-specific cues to segmentation. It is unknown, however, whether performance shown in small-scale laboratory demonstrations of “statistical learning” can scale up to allow learning of the lexicons of natural languages, which are orders of magnitude larger. Artificial language experiments with adults can be used to test whether the mechanisms of statistical learning are in principle scalable to larger lexicons. We report data from a large-scale learning experiment that demonstrates that adults can learn words from unsegmented input in much larger languages than previously documented and that they retain the words they learn for years. These results suggest that statistical word segmentation could be scalable to the challenges of lexical acquisition in natural language learning.     

Twitter Language Use Reflects Psychological Differences between Democrats and Republicans

Previous research has shown that political leanings correlate with various psychological factors. While surveys and experiments provide a rich source of information for political psychology, data from social networks can offer more naturalistic and robust material for analysis. This research investigates psychological differences between individuals of different political orientations on a social networking platform, Twitter. Based on previous findings, we hypothesized that the language used by liberals emphasizes their perception of uniqueness, contains more swear words, more anxiety-related words and more feeling-related words than conservatives’ language. Conversely, we predicted that the language of conservatives emphasizes group membership and contains more references to achievement and religion than liberals’ language. We analysed Twitter timelines of 5,373 followers of three Twitter accounts of the American Democratic and 5,386 followers of three accounts of the Republican parties’ Congressional Organizations. The results support most of the predictions and previous findings, confirming that Twitter behaviour offers valid insights to offline behaviour.     

How arbitrary is language?

It is a long established convention that the relationship between sounds and meanings of words is essentially arbitrary—typically the sound of a word gives no hint of its meaning. However, there are numerous reported instances of systematic sound–meaning mappings in language, and this systematicity has been claimed to be important for early language development. In a large-scale corpus analysis of English, we show that sound–meaning mappings are more systematic than would be expected by chance. Furthermore, this systematicity is more pronounced for words involved in the early stages of language acquisition and reduces in later vocabulary development. We propose that the vocabulary is structured to enable systematicity in early language learning to promote language acquisition, while also incorporating arbitrariness for later language in order to facilitate communicative expressivity and efficiency.     

When It Hurts (and Helps) to Try: The Role of Effort in Language Learning

Compared to children, adults are bad at learning language. This is counterintuitive; adults outperform children on most measures of cognition, especially those that involve effort (which continue to mature into early adulthood). The present study asks whether these mature effortful abilities interfere with language learning in adults and further, whether interference occurs equally for aspects of language that adults are good (word-segmentation) versus bad (grammar) at learning. Learners were exposed to an artificial language comprised of statistically defined words that belong to phonologically defined categories (grammar). Exposure occurred under passive or effortful conditions. Passive learners were told to listen while effortful learners were instructed to try to 1) learn the words, 2) learn the categories, or 3) learn the category-order. Effortful learners showed an advantage for learning words while passive learners showed an advantage for learning the categories. Effort can therefore hurt the learning of categories.     

Distributional Learning of Appearance

Opportunities for associationist learning of word meaning, where a word is heard or read contemperaneously with information being available on its meaning, are considered too infrequent to account for the rate of language acquisition in children. It has been suggested that additional learning could occur in a distributional mode, where information is gleaned from the distributional statistics (word co-occurrence etc.) of natural language. Such statistics are relevant to meaning because of the Distributional Principle that ‘words of similar meaning tend to occur in similar contexts’. Computational systems, such as Latent Semantic Analysis, have substantiated the viability of distributional learning of word meaning, by showing that semantic similarities between words can be accurately estimated from analysis of the distributional statistics of a natural language corpus. We consider whether appearance similarities can also be learnt in a distributional mode. As grounds for such a mode we advance the Appearance Hypothesis that ‘words with referents of similar appearance tend to occur in similar contexts’. We assess the viability of such learning by looking at the performance of a computer system that interpolates, on the basis of distributional and appearance similarity, from words that it has been explicitly taught the appearance of, in order to identify and name objects that it has not been taught about. Our experiment tests with a set of 660 simple concrete noun words. Appearance information on words is modelled using sets of images of examples of the word. Distributional similarity is computed from a standard natural language corpus. Our computation results support the viability of distributional learning of appearance.     

Language proficiency modulates the recruitment of non-classical language areas in bilinguals

Bilingualism provides a unique opportunity for understanding the relative roles of proficiency and order of acquisition in determining how the brain represents language. In a previous study, we combined magnetoencephalography (MEG) and magnetic resonance imaging (MRI) to examine the spatiotemporal dynamics of word processing in a group of Spanish-English bilinguals who were more proficient in their native language. We found that from the earliest stages of lexical processing, words in the second language evoke greater activity in bilateral posterior visual regions, while activity to the native language is largely confined to classical left hemisphere fronto-temporal areas. In the present study, we sought to examine whether these effects relate to language proficiency or order of language acquisition by testing Spanish-English bilingual subjects who had become dominant in their second language. Additionally, we wanted to determine whether activity in bilateral visual regions was related to the presentation of written words in our previous study, so we presented subjects with both written and auditory words. We found greater activity for the less proficient native language in bilateral posterior visual regions for both the visual and auditory modalities, which started during the earliest word encoding stages and continued through lexico-semantic processing. In classical left fronto-temporal regions, the two languages evoked similar activity. Therefore, it is the lack of proficiency rather than secondary acquisition order that determines the recruitment of non-classical areas for word processing.     

A neurocognitive perspective on language: the declarative/procedural model

What are the psychological, computational and neural underpinnings of language? Are these neurocognitive correlates dedicated to language? Do different parts of language depend on distinct neurocognitive systems? Here I address these and other issues that are crucial for our understanding of two fundamental language capacities: the memorization of words in the mental lexicon, and the rule-governed combination of words by the mental grammar. According to the declarative/procedural model, the mental lexicon depends on declarative memory and is rooted in the temporal lobe, whereas the mental grammar involves procedural memory and is rooted in the frontal cortex and basal ganglia. I argue that the declarative/procedural model provides a new framework for the study of lexicon and grammar.     

When Small Words Foretell Academic Success: The Case of College Admissions Essays

The smallest and most commonly used words in English are pronouns, articles, and other function words. Almost invisible to the reader or writer, function words can reveal ways people think and approach topics. A computerized text analysis of over 50,000 college admissions essays from more than 25,000 entering students found a coherent dimension of language use based on eight standard function word categories. The dimension, which reflected the degree students used categorical versus dynamic language, was analyzed to track college grades over students'' four years of college. Higher grades were associated with greater article and preposition use, indicating categorical language (i.e., references to complexly organized objects and concepts). Lower grades were associated with greater use of auxiliary verbs, pronouns, adverbs, conjunctions, and negations, indicating more dynamic language (i.e., personal narratives). The links between the categorical-dynamic index (CDI) and academic performance hint at the cognitive styles rewarded by higher education institutions.     

Modulation of inferotemporal cortex activation during verbal working memory maintenance

Regions of the left inferotemporal cortex are involved in visual word recognition and semantics. We utilized functional magnetic resonance imaging to localize an inferotemporal language area and to demonstrate that this area is involved in the active maintenance of visually presented words in working memory. Maintenance activity in this inferotemporal area showed an effect of memory load for words, but not pseudowords. In the absence of visual input, the selective modulation of this language-related inferotemporal area for the maintenance of words is accompanied by an increased functional connectivity with left prefrontal cortex. These results demonstrate an involvement of inferotemporal cortex in verbal working memory and provide neurophysiological support for the notion that nonphonological language representations can be recruited in the service of verbal working memory. More generally, they suggest that verbal working memory should be conceptualized as the frontally guided, sustained activation of pre-existing cortical language representations.     

Language Acquisition: When Does the Learning Begin?

Language acquisition is quite sophisticated by four months of age. Two cues that babies use to discriminate their language from another are the stress patterns of words and visual cues inherent in language production.