1,721,051 research outputs found
L2 processing as noisy channel language comprehension
The thesis in this paper is that L2 speakers differ from L1 speakers in their ability to do memory storage and retrieval about linguistic structure. We would like to suggest it is possible to go farther than this thesis and develop a computational-level theory which explains why this mechanistic difference between L2 and L1 speakers exists. For this purpose, we believe a noisy channel model (Shannon, 1948; Levy, 2008; Levy, Bicknell, Slattery & Rayner, 2009; Gibson, Bergen & Piantadosi, 2013) could be a good start. Under the reasonable assumption that L2 speakers have a less precise probabilistic representation of the syntax of their L2 language than L1 speakers do, the noisy channel model straightforwardly predicts that L2 comprehenders will depend more on world knowledge and discourse factors when interpreting and recalling utterances (cf. Gibson, Sandberg, Fedorenko, Bergen & Kiran, 2015, for this assumption applied to language processing for persons with aphasia). Also, under the assumption that L2 speakers assume a higher error rate than L1 speakers do, the noisy channel model predicts that they will be more affected by alternative parses which are not directly compatible with the form of an utterance
Large-scale evidence of dependency length minimization in 37 languages
Explaining the variation between human languages and the constraints on that variation is a core goal of linguistics. In the last 20 y, it has been claimed that many striking universals of cross-linguistic variation follow from a hypothetical principle that dependency length—the distance between syntactically related words in a sentence—is minimized. Various models of human sentence production and comprehension predict that long dependencies are difficult or inefficient to process; minimizing dependency length thus enables effective communication without incurring processing difficulty. However, despite widespread application of this idea in theoretical, empirical, and practical work, there is not yet large-scale evidence that dependency length is actually minimized in real utterances across many languages; previous work has focused either on a small number of languages or on limited kinds of data about each language. Here, using parsed corpora of 37 diverse languages, we show that overall dependency lengths for all languages are shorter than conservative random baselines. The results strongly suggest that dependency length minimization is a universal quantitative property of human languages and support explanations of linguistic variation in terms of general properties of human information processing.United States. Dept. of Defense. National Defense Science & Engineering Graduate Fellowship Progra
Cross-linguistic gestures reflect typological universals: A subject-initial, verb-final bias in speakers of diverse languages
In communicating events by gesture, participants create codes that recapitulate the patterns of word order in the world’s vocal languages (Gibson et al., 2013; Goldin-Meadow, So, Ozyurek, & Mylander, 2008; Hall, Mayberry, & Ferreria, 2013; Hall, Ferreira, & Mayberry, 2014; Langus & Nespor, 2010; and others). Participants most often convey simple transitive events using gestures in the order Subject–Object–Verb (SOV), the most common word order in human languages. When there is a possibility of confusion between subject and object, participants use the order Subject–Verb–Object (SVO). This overall pattern has been explained by positing an underlying cognitive preference for subject-initial, verb-final orders, with the verb-medial order SVO order emerging to facilitate robust communication in a noisy channel (Gibson et al., 2013). However, whether the subject-initial and verb-final biases are innate or the result of languages that the participants already know has been unclear, because participants in previous studies all spoke either SVO or SOV languages, which could induce a subject-initial, verb-late bias. Furthermore, the exact manner in which known languages influence gestural orders has been unclear. In this paper we demonstrate that there is a subject-initial and verb-final gesturing bias cross-linguistically by comparing gestures of speakers of SVO languages English and Russian to those of speakers of VSO languages Irish and Tagalog. The findings show that subject-initial and verb-final order emerges even in speakers of verb-initial languages, and that interference from these languages takes the form of occasionally gesturing in VSO order, without an additional bias toward other orders. The results provides further support for the idea that improvised gesture is a window into the pressures shaping language formation, independently of the languages that participants already know. Keywords: Psycholinguistics; Language universals; Language typology; Word order; Gesture; Animac
A Corpus Investigation of Syntactic Embedding in Piraha
The Pirahã language has been at the center of recent debates in linguistics, in large part because it is claimed not to exhibit recursion, a purported universal of human language. Here, we present an analysis of a novel corpus of natural Pirahã speech that was originally collected by Dan Everett and Steve Sheldon. We make the corpus freely available for further research. In the corpus, Pirahã sentences have been shallowly parsed and given morpheme-aligned English translations. We use the corpus to investigate the formal complexity of Pirahã syntax by searching for evidence of syntactic embedding. In particular, we search for sentences which could be analyzed as containing center-embedding, sentential complements, adverbials, complementizers, embedded possessors, conjunction or disjunction. We do not find unambiguous evidence for recursive embedding of sentences or noun phrases in the corpus. We find that the corpus is plausibly consistent with an analysis of Pirahã as a regular language, although this is not the only plausible analysis
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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Investigating Linguistic Biases using the Algorithmic Complexity of Neural Networks
Humans display a strong preference for simple patterns, a bias often dubbed the “simplicity principle” (Chater & Vitanyi, 2003a). This document investigates extensions and problems with this ´ bias. We will begin by an introduction to this bias and why it’s interesting, followed by a primer on algorithmic information theory which is used to formalize it. In Part I we move from there to investigate how algorithmic mutual information can help us understand learning which is facilitated by shared structure across domains, and will then use this (which we dub the “schematicity corollary”) to investigate orthographic transparency. We will find that this approach yields both a principled and good measure of the phenomenon in question. In Part II we will shift focus to an open problem with the simplicity principle: how model representations affect learnability. We will see that approximations of algorithmic information give us a tool to taxonomize learning biases according to the simplicity priors over models under consideration and the expressivity of the model class. We will then use examples from formal language theory (subregularity) to investigate how human-like biases can be affected by model selection and priors over these models. We find that sparsity inducing priors show human like priors, whereas native ANN learning mechanisms do not. We will then conclude with a discussion of these findings, and what additional investigations remain
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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