Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
18265 papers
Evidence on the impact of nature images has been found in research with hospital patients (Ulrich, 2008, Nanda, Hathorn & Neumann, 2007). The use of art in healthcare environments has become increasingly common (Nanda, Eisen & Baladandayuthapani, 2008). Art is viewed as a positive distraction from stress of the hospital among patients and possibly staff (Ulrich et. al. 1991; Ulrich, Zimring, Quan, & Joseph, 2006). In a previous study art preference study (Nanda, Eisen & Baladandayuthapani, 2008) showed significant difference in the ratings of design students and patients. Findings showed that there was a significant difference in the ratings of the two groups. Furthermore, the emotional rating scale (how does the art picture make you feel) was highly correlated to the selection scale (would you put this art picture in your room) for hospital patients- while this was not the case with the design students. What is the role of culture in the above questions and in how does it impact healthcare design?A total of more than 600 design and non-design students from National University of Mexico, National University of Singapore and University of Texas San Antonio rated images of visual art included abstract, representational and nature images from Mexico, Singapore and Texas representative of the unique cultural contexts, in addition to images that strictly adhere to the evidence-based guidelines for healthcare art laid down by Ulrich & Gilpin (2003) and examples of classic high art.At the end of the survey students re-rated the images again as if they were hospitalized and lying in a patient room. An analysis of preferences across cultures, design disciplines and emotion and selection was undertaken.Results show a surprising amount of agreement across cultures on image rating for hospital rooms. Level of agreement for art selection for personal rooms is significantly lower. This is true in both design and non-design students. Landscapes with a high depth of field, bright colors and verdant foliage were rated consistently high across all cultures, regardless of indigenous elements, with few exceptions, that suggests that there is a certain universal appeal for restorative images of nature that go beyond cultural and educational boundaries. The study showed that empathy (how this art would make you feel) is a stronger determinant of selection than culture, or education, when it comes to art selection for hospitals.
Les enquêtes expérimentales du projet de l’Atlas linguistique du Brésil ont montré, dans l’État du Ceará, une variation lexicale extrêmement importante, pouvant comporter en plus d’une variation diatopique, une variation diastratique, dans le parler régional de cet État. Ayant travaillé sur les variantes populaires du portugais du Nordeste du Brésil, spécialement dans les États de la Paraíba et du Ceará, auxquels nous avons consacré une bonne partie de nos études, nous pouvons nous interroger sur ce qui est régional, ce qui est populaire, ce qui est de la créativité, non seulement des auteurs mais des locuteurs en général. Les réponses à ces questions sont souvent difficiles, voire ambiguës car tout locuteur réalise ces fonctions dans chaque acte de discours, en les intercalant, les mélangeant, donnant plus d’emphase à l’une ou à l’autre. Près d’une dizaine de dictionnaires, vocabulaires et glossaires sur le « cearês » (le parler du Ceará) ont paru ces dernières décennies et spécialement au cours des deux dernières années, montrant toutes les variations lexicales, qui dans certains cas ne sont pas seulement du Ceará mais de tout le Nordeste. Dans les exemples que nous montrons ici, nous rencontrons des cas de néologismes lexicaux et sémantiques, d’apparition de nouveaux termes à partir de modifications phonétiques, en plus d’usages de termes déjà enregistrés dans les dictionnaires de normes officielles mais avec un sens différent et des termes qui ne sont rencontrés que dans les dictionnaires régionaux populaires du Ceará et non attestés en discours. Tous ces termes sont des variantes diatopiques du Ceará, diastratiques, de classes moins scolarisées, ou diaphasiques, représentatifs du style de l’auteur ou d’une tranche d’âge de la population. Ces variantes coexistent, et elles sont renforcées ou non, à chaque instant, en fonction du contexte non seulement linguistique, mais, surtout extralinguistique dans lequel elles se produisent.
Semantic verbal fluency (SVF) often shows early and disproportionate decline in AD relative to other language, attention, and executive abilities. Successful performance on SVF depends on the ability to organize conceptual information into related clusters and efficiently access these clusters. Current methods for clustering and switching assessment are labor-intensive and subjective. We developed an automated computational linguistic approach to quantify the semantic content of SVF responses. Neuropsychological and resting state fMRI data were obtained from the work-up of 52 patients presenting to the Minneapolis VAMC GRECC Memory Loss Clinic. Participants included had a clinical diagnosis of MCI or AD, a completed MRI protocol with good quality data, and neuropsychological evaluation including the SVF task (animals). Imaging data were collected on a Philips 1.5T system at the Minneapolis VAMC. Semantic indices based on pairs of words on the SVF task were quantified in two ways: based on the length of their hierarchical relations in WordNet, an electronic lexical database of English (similarity), or calculated using a computerized algorithm based on a variant of principal components analysis (relatedness). Mean cumulative and sequential indices were produced for each method: cumulative similarity and relatedness were computed between all possible pairs of words produced regardless of order; and sequential similarity and relatedness were computed only between pairs of adjacent words. Higher scores reflect larger clusters and reduced switching. Several resting state fMRI network measures were related to the four automated semantic fluency indices. Nodal diversity, local efficiency, and the mean clustering coefficient, were all significantly correlated with cumulative and sequential measures of semantic similarity and relatedness. Pearson r values ranged from.323-.407 with corresponding p-values of.012-.003. All correlations survived multiple comparison correction. The traditional SVF score was not significantly related to imaging indices. We found that computational linguistic measurements of similarity and relatedness were significantly related to network measures obtained from resting state fMRI. These results suggest automated assessment of SVF has correlates with brain function in MCI and AD, and may outperform the traditional SVF score. This approach provides an easy way to standardize clustering and switching assessment without adding burden.
Medical discharge documents are summaries written by a physician about the patient’s condition and aim at transferring information to other health care personnel but also to the patient. According to the legislation, the patient should be able to understand the document. In practice, however, this has been shown to be problematic. This paper studies discharge documents from the patients’ perspective and examines how they fulfil the legislation’s demands on understandability. Concentrating on the vocabulary of the texts, we analyse the frequency of domainadapted terms, abbreviations and foreign words. The material consists of 23 528 heart patients’ discharge documents (5 747 126 words). The analysis is performed with the morphological analyser FinTWOL (http://www2.lingsoft.fi/cgi-bin/fintwol). Altogether, FinTWOL analyses 24% of the corpus as unknown or foreign words, abbreviations or medical terms. The most common category, unknown words, includes misspellings and medical terms, such as l.dex. Of these, 100 most common cover for 43% of the total. These terms thus seem to be relatively fixed. Of the words analysed as abbreviations, some are common also in standard language, but others are still very domain-specific, such as I.V. (intravenous). Also the used abbreviations are very fixed: the 100 most common ones cover for 94% of the total. This, however, does not help the patient who probably reads only one document. Similarly, even though misspellings are globally infrequent, they still occur more than once per document. In order to place the obtained results in a context, we performed a similar analysis on general Finnish university newspaper text from Turku Dependency Treebank. In comparison with the 24% obtained with the discharge documents, from the total of 10 687 words, 8,6% were given a special tag. The results show that that terms and abbreviations are considerably more used in discharge documents than in general newspaper text. It is clear that a text with such a vocabulary is domain-specific and distinct from the language that the patient is used to. Also e.g. the varying use of upper and lower case letters (dg and DG for diagnosis) emphasize the particularity of the language. In standard language texts such writing would not be acceptable. Standard writing would, however, help the patients to better understand the texts.
We often use tactile-input in order to recognize familiar objects and to acquire information about unfamiliar ones. We also use our hands to manipulate objects and utilize them as tools. However, research on object affordances has mainly been focused on visual-input and, thus, limiting the level of detail one can get about object features and uses. In addition to the limited multisensory-input, data on object affordances has also been hindered by limited participant input (e.g., naming task). In order to address the above mention limitations, we aimed at identifying a new methodology for obtaining undirected, rich information regarding people’s perception of a given object and the uses it can afford without necessarily viewing the particular object. Specifically, 40 participants were video-recorded in a three-block experiment. During the experiment, participants were exposed to pictures of objects, pictures of someone holding the objects, and the actual objects and they were allowed to provide unconstrained verbal responses on the description and possible uses of the stimuli presented. The stimuli presented were lithic tools given the: novelty, man-made design, design for specific use/action, and absence of functional knowledge and movement associations. The experiment resulted in a large linguistic database, which was linguistically analyzed following a response-based specification. Analysis of the data revealed significant contribution of visual- and tactile-input in naming and definition of object-attributes (color/condition/shape/size/texture/weight), while no significant tactile-information was obtained for object-features of material, visual-pattern, and volume. Overall, this new approach highlights the importance of multisensory-input in the study of object affordances.
The task of automatic machine translation (MT) is the focus of a huge variety of active research efforts, both because of the intrinsic utility of this difficult task, and the theoretical and linguistic insights that arise from modeling relationships between natural languages. However, MT systems that leverage syntactic information are only recently becoming practical, and in a typical system of this sort, syntactic information is generated by monolingual parsers; the task of explicitly modeling syntactic relationships between target and source languages is yet to be fully explored. This thesis investigates the problem of finding syntactic parse trees of target and/or source sentences that are more appropriate for use in a syntactic MT system. Two basic methodologies are explored. First, we present a sequence of two statistical models that leverage bilingual information to improve the linguistic quality of syntactic parses, as measured by their ability to replicate human-generated gold-standard annotations. The first model uses word to word alignments as an external source of information, while the second models the alignments jointly. These models are both quite effective at improving the intrinsic quality of the parse trees, and the second model additionally improves word alignment performance. However, while the two models achieve similar parsing improvements, we find that improving parses in conjunction with word alignments is much more helpful for the downstream machine translation task. In the next part of the thesis, we explore this finding further by investigating the effects on MT performance of agreement between parse trees and word alignments. We present a simple method for transforming input trees in a way that ignores gold-standard annotations, concentrating instead on improving syntactic agreement directly. In experiments, we find that though we obviously lose fidelity to more linguistically informed treebank annotation guidelines, this transformation-based approach yields the strongest improvements in syntactic machine translation.
This dissertation explores the nature and extent of retroflex consonant harmony in South Asia. Using statistics calculated over lexical databases from a broad sample of languages, the study demonstrates that retroflex consonant harmony is an areal trait affecting most languages in the northern half of the South Asian subcontinent, including languages from at least three of the four major families in the region: Dravidian, Indo-Aryan and Munda (but not Tibeto-Burman). Dravidian and Indo-Aryan languages in the southern half of the subcontinent do not exhibit retroflex consonant harmony. In South Asia, retroflex consonant harmony is manifested primarily as a static co-occurrence restriction on coronal consonants in roots/words. Historical-comparative evidence reveals that this pattern is the result of retroflex assimilation that is non-local, regressive and conditioned by the similarity of interacting segments. These typological properties stand in contrast to those of other retroflex assimilation patterns, which are local, primarily progressive, and not conditioned by similarity. This is argued to support the hypothesis that local feature spreading and long-distance feature agreement constitute two independent mechanisms of assimilation, each with its own set of typological properties, and that retroflex consonant harmony is the product of agreement, not spreading. Building on this hypothesis, the study offers a formal account of retroflex consonant harmony within the Agreement by Correspondence (ABC) model of Rose & Walker (2004) and Hansson (2001; 2010). Two Indo-Aryan languages, Kalasha and Indus Kohistani, figure prominently throughout the dissertation. These languages exhibit similarity effects that have not been clearly observed in other retroflex consonant harmony systems; retroflexion is contrastive in both non-sibilant (i.e., plosive) and sibilant obstruents (i.e., affricates and fricatives), but harmony applies only within each manner class, not between them. At the same time, harmony is not sensitive to laryngeal features. Theoretical implications of these and other similarity effects are discussed.
New Irish speakers in Belfast play a crucial, complex part in the revitalization and change of both the city and Irish within Northern Ireland. This paper examines the role of new Irish speakers in transforming Belfast, whose emergence from a post-conflict period involves a reassessment of communal cultural expressions. Markers of ethno-national identity are bitterly contentious locally, and yet increasingly celebrated, in line with international trends, as high status cultural forms and potentially profitable tourist attractions. Irish in Belfast currently occupies an ambiguous position: divisive enough for a sign reading ‘Happy Christmas’ in Irish to be experienced as an insult by some city councillors, yet a secure enough part of the establishment for a neighbourhood to be officially rebranded as the Gaeltacht Quarter. <br/>When, how and where new Irish speakers use the language in Belfast has implications for the relationship of Irishness to the Northern Irish state and for the place of Belfast within regional frameworks across the UK, Ireland and Europe. Adult learners and young people exiting Irish medium education have an impact on life in Belfast beyond its small population of Irish speakers. Urbanisation fuelled by new speakers, which shifts the balance of Irish language resources and speakers away from traditional rural Gaeltacht areas and towards cities, also has implications for the language itself. Recent increase in new Irish speakers in Belfast is due to expansion in the Irish-medium sector as well as to adult learners, whose decisions contribute to the school expansion. <br/>Urbanisation, multilingualism and intergenerational shift combine in Belfast to produce new linguistic norms. Moreover, in a minority language community where hierarchies of ‘authenticity’ are weighted towards the rural and the native speaker, where the rural and the native have traditionally been conflated, and where indigeneity is a central concept to contested nationalisms, the emergence of a self-confident, youthful Irish speaking community in Northern Ireland’s biggest city involves a recalibration of the qualities signifying ‘gaelicness’. As students, professionals, hobbyists and activists, new Irish speakers in Belfast occupy a vital position at the crux of changing ideas about place, language and identity.<br/>
Early-latency theories of emotional processing state that at least coarse monitoring of the emotional valence (a pleasure-displeasure continuum) of facial expressions should be both rapid and highly automated (LeDoux, 1995; Russell, 1980). Research has largely substantiated early-latency differential processing of emotional versus non-emotional facial expressions; however, the effect of valence on early-latency processing of emotional facial expression remains unclear. In an effort to delineate the effects of valence on early-latency emotional facial expression processing, the current investigation compared ERP responses to positive (happy and surprise), neutral, and negative (afraid and sad) basic facial expression photographs as well as to positive (happy-surprise), neutral (afraid-surprise, happy-afraid, happy-sad, sad-surprise), and negative (sad-afraid) morph facial expression photographs during a valence-rating task. Morphing manipulations have been shown to decrease the familiarity of facial patterns and thus preclude any overlearned responses to specific facial codes. Accordingly, it was proposed that morph stimuli would disrupt more detailed emotional identification to reveal a valence response independent of a specific identifiable emotion (Balconi & Lucchiari, 2005; Schweinberger, Burton & Kelly, 1999). ERP results revealed early-latency differentiation between positive, neutral, and negative morph facial expressions approximately 108 milliseconds post-stimulus (P1) within the right electrode cluster; negative morph facial expressions continued to elicit significantly smaller ERP amplitudes than other valence categories approximately 164 milliseconds post-stimulus (N170). Consistent with previous imaging research on emotional facial expression processing, source localization revealed substantial dipole activation within regions of the mesolimbic dopamine system. Thus, these findings confirm rapid valence processing of facial expressions and suggest that negative valence processing may continue to modulate subsequent structural facial processing.
Individuals who effectively regulate or mildly increase their systolic blood pressure (SBP) in response to an orthostatic challenge exhibit healthier affective status, cognitive functioning, and better quality of life. Thus, increased SBP in response to an orthostatic challenge serves as a proxy for several underlying changes. This study examined the relationship between SBP regulation and self-esteem in children. Data were collected from 92 boys and girls, aged 8–11 years. Systolic, diastolic, and pulse measurements were obtained after 5 minutes of remaining supine and again after 1 minute of standing. Children also provided affective ratings on the Children's Depression Inventory. The Negative Self-Esteem subscale was examined for this study. A multiple regression analysis revealed that poorer orthostatic regulation was associated with higher levels of negative self-esteem among children aged 8–11 years. Thus, orthostatic BP regulation may serve as a biological marker for poor self-esteem in children. This may have further implications for children's emotional functioning as low self-esteem may serve as a risk factor for future negative affective states.
Alexithymia is a personality trait characterised by difficulties in identifying and describing one’s emotions, constricted imaginal processing, and an externally oriented cognitive style. Alexithymia is associated with psychopathology and interpersonal problems. The aim of the current study was to evaluate the psychometric properties of the most frequently used measure of alexithymia, the self-report 20-item Toronto Alexithymia Scale (TAS-20). Specifically, the study aimed to (1) cross-validate the hypothesised three-factor structure of the TAS-20, (2) determine whether the measure indirectly assesses the constricted imaginal thinking component of alexithymia, despite its absence of imagination items, (3) examine the overlap between the TAS-20 and measures of psychopathology, and (4) determine whether the TAS-20 assesses actual, rather than merely perceived, emotional understanding. Participants were 194 (138 female) university students and community members who completed an online survey. Confirmatory factor analyses showed mixed support for the hypothesised three-factor model of the TAS-20; however, this model provided a better fit to the data than either a one- or two-factor model. Inverse relationships were found between the TAS-20 and measures of perspective-taking and fantasy (although this relationship was only marginally significant for fantasy). There were moderate to large positive associations between the TAS-20 and measures of depression, anxiety, stress, and negative affectivity. Inverse relationships were found between the TAS-20 and objective measures of emotional ability; however, these relationships were no longer significant after the effects of negative emotions and affectivity were partialled out. Higher TAS-20 scores were also associated with more moderate affective valence ratings of emotion-evoking stimuli, and thus lower self-reported arousal. Together, these findings suggest problems with the TAS-20’s construct validity. Theoretical and practical implications are discussed.
This paper focuses on the links between contemporary literature and the various positions choosenchosenby authors facing the problematics of translation. Beginning with the observation that translation studies should develop from a theoretical point of view in Japan--an emblematic country for translations--this paper shows that currently, translation in Japan has to be considered as a cultural exportation trend and not only as the importation trend that dominated the cultural scene during the 20th century. For example, data on published translations in France show that since 2007, Japanese is the second most frequently translated language after American-English--due to the popularity of mangas in France. In the literary field, new phenomenons can also be observed in Japan. In this paper, four case studies are presented. The most remarkable case concerns Murakami Haruki's strategy, in which he, being an important translator of the Great American Novel, crosses the boundaries between countries and languages in order to represent a new kind of nationless writer, i.e. a global writer appreciated all over the world. On the other hand, Mizumura Minae mixes English and Japanese in her I novel from left to right, making it untranslatable into English. This for her represents the resistance of a minor language, Japanese, to the domination of English. Tawada Yôko, for her part, writes in two languages, Japanese and German, and in doing so tries to deconstruct both cultural and linguistic norms, enhancing translation as an impossible tool. Finally, the American-born Hideo Levy's three-piece band features Japanese, English and Chinese members, interconnected by the belief in translation as an ideal vector of communication. All these new streams contribute to the reshifting of Japanese literature in the world and induce a necessary renewal of the critical approaches.
The explosion of information in the World Wide Web is overwhelming readers with limitless information. Large internet articles or journals are often cumbersome to read as well as comprehend. More often than not, readers are immersed in a pool of information with limited time to assimilate all of the articles. It leads to information overload whereby readers are trying to deal with more information than they can process. Hence, there is an apparent need for an automatic text summarizer as to produce summaries quicker than humans. The text summarization research on mobile platform has been inspired by the new paradigm shift in accessing information ubiquitously at anytime and anywhere on Smartphones or smart devices. In this research, a semantic and syntactic based summarization is implemented in a text summarizer to solve the overload problem whilst providing a more coherent summary. Additionally, WordNet is used as the lexical database to semantically extract the text document which provides a more efficient and accurate algorithm than the existing summary system. The objective of the paper is to integrate WordNet into the proposed system called TextSumIt which condenses lengthy documents into shorter summarized text that gives a higher readability to Android mobile users. The experimental results are done using recall, precision and F-Score to evaluate on the summary output, in comparison with the existing automated summarizer. Human-generated summaries from Document Understanding Conference (DUC) are taken as the reference summaries for the evaluation. The evaluation of experimental results shows satisfactory results.
Statistické jazykové modely jsou důležitou součástí mnoha úspěšných aplikací, mezi něž patří například automatické rozpoznávání řeči a strojový překlad (příkladem je známá aplikace Google Translate). Tradiční techniky pro odhad těchto modelů jsou založeny na tzv. N-gramech. Navzdory známým nedostatkům těchto technik a obrovskému úsilí výzkumných skupin napříč mnoha oblastmi (rozpoznávání řeči, automatický překlad, neuroscience, umělá inteligence, zpracování přirozeného jazyka, komprese dat, psychologie atd.), N-gramy v podstatě zůstaly nejúspěšnější technikou. Cílem této práce je prezentace několika architektur jazykových modelůzaložených na neuronových sítích. Ačkoliv jsou tyto modely výpočetně náročnější než N-gramové modely, s technikami vyvinutými v této práci je možné jejich efektivní použití v reálných aplikacích. Dosažené snížení počtu chyb při rozpoznávání řeči oproti nejlepším N-gramovým modelům dosahuje 20%. Model založený na rekurentní neurovové síti dosahuje nejlepších publikovaných výsledků na velmi známé datové sadě (Penn Treebank).
Linguistic Thought of the Spanish Renaissance and HumanismThe present article examines the linguistic thoughts of the period of the Humanism and Renaissance in Spain comparing with the case of Italy.In Spain, in the end of the 15th century, the philologist Antonio de Nebrija introduced the humanisitic ideas born in Italy, and applied them not only to reform the education of the Latin or the studies of letters in general but also to create the grammar of a vernacular castillian language.In Italy, already in the 14th century, there were great works of literature written by the three most brilliant authors; Dante, Boccaccio and Petrarca.Then during the next two centuries the debates surround the language got intense, and the intellectuals discussed the question of how to establish linguistic norms and codify the language, that is to say which dialect or speech of Italy -like the Tuscan-should be standard of the whole Italian peninsula.This called questione della lingua"question of the language" no longer was a problem exclusively in Italy, rather than the problem of the whole Europe.In Spain, due to its proximity to Italy, that current of thought was introduced and developed pronto.But while then Italy was divided into a number of warring city-states that have distinctive dialects for each, in Spain, contrastively, there was a strong centralized government due to the union of Castille and Aragon in the latter half of the 15th century.This difference of political situations made different atmosphere in the debates about language in each of the two peninsulas.I will describe what was the "questions of the language" and how developed this both in Italy and in Spain.
This paper is stimulated by the ideas of Karel Hausenblas, the work of Olga Müllerová and the research on the syntax of Czech dialects (J. Balhar, J. Chloupek, M. Šipková and others). It presents a catalogue of phenomena and means of expression which mark the syntax of spoken Czech and devotes attention above all to: a) special syntactic constructions b) the varying formation of transitions between syntactic units in spoken expression (sharply structured transitions) and in written expression (softer, less apparent transitions, couched or “stuck” with numerous redundant means with non-definite semantics); that is, differences in the degree and type of cohesion, connection, or glutination between written and spoken expression c) differences between condensed, constricted written syntax and the relaxed structure of syntactic units in spoken Czech (with the prevalence of parataxis and juxtaposition). The paper views the syntactic differences between written and spoken expression as stylistic differences. It is based on data from various corpora of spoken Czech (including the Prague Dependency Treebank of Spoken Czech) and on the comparison of written and spoken narrative by the same speaker/author.
It is said that Vietnamese is a language with highly ambiguous words. However, there has been no published Word Sense Disambiguation (WSD hereafter) research on this language. This current research is the first attempt to study Vietnamese WSD. Especially, we would like to explore the effective features for training WSD classifiers and verify the applicability of the ‘pseudoword’ technique to both investigating effectiveness of features and training WSD classifiers. Three tasks have been conducted, using two corpora which were built manually based on Vietnamese Treebank and automatically by applying pseudowords technique. Experiment results showed that Bag-Of-Word feature performs well for all three categories of words (verbs, nouns, and adjectives). However, its combination with POS, Collocation or Syntactic features can not significantly improve the performance of WSD classifiers. Moreover, the experiment results confirmed that pseudoword is a suitable technique to explore the effectiveness of features in disambiguation of Vietnamese verbs and adjectives. Furthermore, we empirically evaluated the applicability of the pseudoword technique as an unsupervised learning method for real Vietnamese WSD.
OBJECTIVE: It has traditionally been thought that covert face recognition cannot be observed in developmental cases of prosopagnosia, because the phenomenon is thought to rely on the activation of face representations created during a period of normal processing. Yet, recent studies have provided evidence of covert recognition in some developmental cases, and critically the findings of one study suggest that these individuals might be processing faces on an affective dimension rather than a familiarity dimension. The current study aimed to examine this possibility using a physiological measure of covert recognition, the skin conductance response (SCR). METHOD: One 61-year-old male with developmental prosopagnosia and 10 age-matched (M = 59.80 years, SD = 4.02) controls (5 men) took part in this study. Participants viewed a set of 15 famous faces intermixed with 30 novel faces, and the SCR was recorded throughout. RESULTS: Although control participants demonstrated an increased SCR for famous faces in comparison with novel faces, t(9) = 2.112, p =.032, d =.382, the same finding was not observed in Patient WS. However, when WS' increase in SCR was correlated with his affective ratings of the celebrities from name cues, a strong negative correlation was observed (r = -.614, n = 34, p =.020). CONCLUSION: This pattern of findings was interpreted as evidence that WS is covertly processing faces on an affective dimension rather than a familiarity dimension, and fits well with recent neurophysiological findings that support hypotheses for independent processing of cognitive and affective information.
The Quran is a significant religious text written in a unique literary style, close to very poetic language in nature. Accordingly it is significantly richer and more complex than the newswire style used in the previously released Arabic PropBank (Zaghouani et al., 2010; Diab et al., 2008). We present preliminary work on the creation of a unique Arabic proposition repository for Quranic Arabic. We annotate the semantic roles for the 50 most frequent verbs in the Quranic Arabic Dependency Treebank (QATB) (Dukes and Buckwalter 2010). The Quranic Arabic PropBank (QAPB) will be a unique new resource of its kind for the Arabic NLP research community as it will allow for interesting insights into the semantic use of classical Arabic, poetic literary Arabic, as well as significant religious texts. Moreover, on a pragmatic level QAPB will add approximately 810 new verbs to the existing Arabic PropBank (APB). In this pilot experiment, we leverage our knowledge and experience from our involvement in the APB project. All the QAPB annotations will be made freely available for research purposes. 1
This study investigated the effect of arousal on short-term relational memory and its underlying cortical network. Seventeen healthy participants performed a picture by location, short-term relational memory task using emotional pictures. Functional magnetic resonance imaging was used to measure the blood-oxygenation-level dependent signal relative to task. Subjects' own ratings of the pictures were used to obtain subjective arousal ratings. Subjective arousal was found to have a dose-dependent effect on activations in the prefrontal cortex, amygdala, hippocampus, and in higher order visual areas. Serial position analyses showed that high arousal trials produced a stronger primacy and recency effect than low arousal trials. The results indicate that short-term relational memory may be facilitated by arousal and that this may be modulated by a dose-response function in arousal-driven neuronal regions.
This paper presents a conditional random fields based labeling approach to Chinese punctuation prediction.To this end, we first reformulate Chinese punctuation prediction as a multiple-pass labeling task on a sequence of words, and then explore various features from three linguistic levels, namely words, phrase and functional chunks for punctuation prediction under the framework of conditional random fields.Our experimental results on the Tsinghua Chinese Treebank show that using multiple deeper linguistic features and multiple-pass labeling consistently improves performance.
An initiative to model a Bangla to English (B2E) translation using Natural Language Processing (NLP) was proposed in our previous research. Here we implemented the model with a lot of modifications. A very successful translator is observed in Anubadok Online which is based on Penn Treebank annotation system and it can only translate English sentences to Bangla. Penn Tree Bank is the collection of English corpus, so Bangle linguistic processing is not observed there. Bangla is an Irregular Language. In our previous research, we proposed a case structure analysis for verb. There are a lot of influences of case in Bangla language. The relationship between verb and case elements is an important issue for Bangla language. But in our current implementation we used rule based approach. For Bangla-English translation first we performed morphological analysis for Bangla then we used rule based analysis where we considered a limited feature of case analysis. After that, using a dictionary we translate bangle words into English. To make an English sentence, we considered English SVO grammatical rules. Our current system is successfully implemented for the translation of Assertive-Affirmative, Negative and Interrogative sentences.
When porting parsers to a new domain, many of the errors are related to wrong attachment of out-of-vocabulary words. Since there is no available annotated data to learn the attachment preferences of the target domain words, we attack this problem using a model of selectional preferences based on domainspecific word classes. Our method uses Latent Dirichlet Allocations (LDA) to learn a domain-specific Selectional Preference model in the target domain using un-annotated data. The model provides features that model the affinities among pairs of words in the domain. To incorporate these new features in the parsing model, we adopt the co-training approach and retrain the parser with the selectional preferences features. We apply this method for adapting Easy First, a fast nondirectional parser trained on WSJ, to the biomedical domain (Genia Treebank). The Selectional Preference features reduce error by 4.5 % over the co-training baseline. 1
Ontology matching is a main step for integrating overlapping domains of knowledge and establishing interoperation among semantic web application. As information sources grow rapidly, manual ontology matching becomes more tedious and time-consuming and consequently leads to errors and frustration. In this paper we developed the new lexical and semantic similarity measure by using the lexical database ConceptNet. The proposed strategy used new lexical and semantic matching for finding the correspondence entities. In the semantic approach we use the electronic lexical database, ConceptNet for identifying the similar entities and create similarity matrices according to that. We evaluate the proposed measure using standard methods of precision and recall, tested on a well- known benchmark and also compared to other algorithms presented in the paper. The experimental results show the proposed algorithm is effective and outperforms other algorithms.
This paper presents a novel top-down head-driven parsing algorithm for data-driven projective dependency analysis. This algorithm handles global structures, such as clause and coordination, better than shift-reduce or other bottom-up algorithms. Experiments on the English Penn Treebank data and the Chinese CoNLL-06 data show that the proposed algorithm achieves comparable results with other data-driven dependency parsing algorithms.
This article, drawing upon Juraj Dolnik's book on the theory of standard language with regard to standard Slovak (2010), concentrates on the question of the sources of standard variety and the problem of objectivity of scientific knowledge. Reconsidering Dolnik's concept of norm critically, it places emphasis on the fact that linguistic norms, as a part of social norms, are constituted in interactions, which helps to explain their indexicality. It also argues that language users are actors in social processes who hold specific social roles, which corresponds to their dif- fering power (and vice versa). Referring to Language Management Theory, the article concludes with some more general arguments in favor of qualitative methodology in the research on linguistic norms and the standard variety.
Research suggests that psychological stress can exacerbate allergies, but relatively little is known about the effect of stress on mucosal immune processes central to allergic pathophysiology. In this study, we quantified vascular endothelial growth factor (VEGF), interferon gamma (IFN-γ), and interleukin-4 concentrations in saliva (S) and exhaled breath condensate (EBC) during final exams and at midsemester among 23 healthy and 21 allergic rhinitis individuals. IFN-γs decreased during exams for both groups while VEGF(EBC) increased (and increases in VEGFs were a trend). Elevated negative affect ratings predicted higher VEGF(EBC) in allergic individuals. IFN-γ(EBC) increased in healthy individuals early during exams and then decreased, while allergic individuals showed a decrease in IFN-γ(EBC) throughout final exams. These findings suggest that psychological stress can suppress cellular immune function among allergic individuals while increasing VEGF.
This paper discusses an automatic way to derive a type hierarchy for verbal items in Korean based on their subcategorization. There are three steps: First, all the dependent categories of the each verb are extracted from the Sejong Treebank. Second, based on the frequency of the dependent categories of each verb, the most stable subcategorization frames are selected, and two statistical measures are tested with some variations in their cutoff values. The resulting subcategorization frames are then compared with those from the Sejong Electronic dictionary for evaluation. The final step is to form a type hierarchy for Korean verbal items, based on the chosen subcategorization information.
Combinatory Categorial Grammar (CCG) is an expressive grammar formalism which is able to capture long-range dependencies. However, building large and wide-coverage treebank for CCG is expensive and time-consuming. In this paper, we focus on the problem of unsupervised CCG induction from plain texts. Based on the baseline model in (Bisk and Hockenmaier, 2012), we propose following two improvements: (1) we utilize boundary part-of-speech (POS) tags to capture lexical information; (2) we perform nonparametric Bayesian inference based on the Pitman-Yor process to learn compact grammars. Experiments on English Penn treebank demonstrate the effectiveness of our boundary model and Bayesian learning.
BACKGROUND: Hypochondriacal attitudes were associated with cognitions not related to illness: Social fears, low self-esteem, and reduced warm glow effect, i.e. less positive appraisal of familiar stimuli. Only a single study had investigated the correlation of hypochondriacal attitudes with the warm glow effect so far and the present study aimed to corroborate this association. Particularly, the present investigation tested for the first time whether social fears, low self-esteem, and reduced warm glow effect represent distinct or related biases in hypochondriacal attitudes. METHODS: Fifty-five volunteers filled in the Hypochondriacal Beliefs and Disease Phobia scales of the Illness Attitude Scales, two scales enquiring social fears of criticism and intimacy, and the Rosenberg Self-Esteem Scale. The interaction of valence and spontaneous familiarity ratings of Chinese characters indicated the warm glow effect. RESULTS: A stepwise regression model revealed specific covariance of social fears and warm glow with hypochondriacal attitudes independent from the respective other variable. The correlation between low self-esteem and hypochondriacal attitudes missed significance. CONCLUSIONS: Hypochondriacal attitudes are embedded in a heterogeneous cluster of non-illness-related cognitions. Each social fears and a reduced cognitive capacity to associate two features--positive appraisal and familiarity--could diminish the susceptibility to safety signals such as medical reassurance. To compensate for reduced susceptibility to safety signals, multifocal treatment and repeated consultations appear advisable.
Visual characteristics are important factors in the transmission of images and animation for semantic interpretation; they have the functions of symbolic conversion and representation of the information content, and are also media between the viewer and the information in the image cognition process. The author had published the related researches for discussions of spreading on semantic network, and deeply investigated on image cognitions of Chinese poetry. This study applied content brainstorming narrative methods to engage in exploration of spreading activation model (SAM), and used the poetry of Wang Wei, who is known as the Buddha of Ancient Chinese poetry, Autumn Evening in the Mountains, to collect keywords for textual association and interpretation. This study also designed visual images that correspond to the associated keywords, based on dynamic visual focus of image content. Finally, this study selected 20 fourth grade students in Taiwan as the test subjects, and the experiment method was used to collect the described associations of students after they viewed the images, the lexical database formed by spreading vocabulary. The research findings aim to help explore interpretive relationship between the texts and images in poetry, providing a reference basis for visual transmission design.
In this paper we first describe the technology of automatic annotation transformation, which is based on the annotation adaptation algorithm (Jiang et al., 2009). It can automatically transform a human-annotated corpus from one annotation guideline to another. We then propose two optimization strategies, iterative training and predict-self reestimation, to further improve the accuracy of annotation guideline transformation. Experiments on Chinese word segmentation show that, the iterative training strategy together with predictself reestimation brings significant improvement over the simple annotation transformation baseline, and leads to classifiers with significantly higher accuracy and several times faster processing than annotation adaptation does. On the Penn Chinese Treebank 5.0, it achieves an F-measure of 98.43%, significantly outperforms previous works although using a single classifier with only local features. 1
WordNet proved that it is possible to construct a large-scale electronic lexical database on the principles of lexical semantics. It has been accepted and used extensively by computational linguists ever since it was released. Inspired by WordNet's success, we propose as an alternative a similar resource, based on the 1987 Penguin edition of Roget's Thesaurus of English Words and Phrases. Peter Mark Roget published his first Thesaurus over 150 years ago. Countless writers, orators and students of the English language have used it. Computational linguists have employed Roget's for almost 50 years in Natural Language Processing, however hesitated in accepting Roget's Thesaurus because a proper machine tractable version was not available. This dissertation presents an implementation of a machine-tractable version of the 1987 Penguin edition of Roget's Thesaurus - the first implementation of its kind to use an entire current edition. It explains the steps necessary for taking a machine-readable file and transforming it into a tractable system. This involves converting the lexical material into a format that can be more easily exploited, identifying data structures and designing classes to computerize the Thesaurus. Roget's organization is studied in detail and contrasted with WordNet's. We show two applications of the computerized Thesaurus: computing semantic similarity between words and phrases, and building lexical chains in a text. The experiments are performed using well-known benchmarks and the results are compared to those of other systems that use Roget's, WordNet and statistical techniques. Roget's has turned out to be an excellent resource for measuring semantic similarity; lexical chains are easily built but more difficult to evaluate. We also explain ways in which Roget's Thesaurus and WordNet can be combined.
A novel statistical linguistic feature, called punctuation confidence, is proposed in this paper for assisting in prosodic break prediction in Mandarin text-to-speech. The punctuation confidence calculated from the input text is a measure of the likelihood of inserting a major PM at a word boundary. Since a punctuation in text tends to be pronounced as a break, the punctuation confidence associated with a punctuation estimate should provide useful information for break prediction from text. The idea is realized in this study by first employing a conditional random field (CRF)-based model to generate a predicted punctuation and its associated punctuation confidence for each word boundary. Then, the predicted punctuation and its punctuation confidence are combined with contextual linguistic features to predict the break type of the word boundary by an MLP (multi-layer perceptrons). Experiment on the Treebank speech corpus confirmed the effectiveness of the proposed approach.
The GF Eclipse Plugin provides an integrated development environment (IDE) for developing grammars in the Grammatical Framework (GF). Built on top of the Eclipse Platform, it aids grammar writing by providing instant syntax checking, semantic warnings and cross-reference resolution. Inline documentation and a library browser facilitate the use of existing resource libraries, and compilation and testing of grammars is greatly improved through single-click launch configurations and an in-built test case manager for running treebank regression tests. This IDE promotes grammar-based systems by making the tasks of writing grammars and using resource libraries more efficient, and provides powerful tools to reduce the barrier to entry to GF and encourage new users of the framework.
This paper outlines the design principles and choices, as well as the ongoing development process of the Common Orthographic Vocabulary of the Portuguese Language (VOC), a large scale electronic lexical database which was adopted by the Community of Portuguese-Speaking Countries ’ (CPLP) Instituto Internacional da Língua Portuguesa to implement a spelling reform that is currently taking place. Given the different available resources and lexicographic traditions within the CPLP countries, a range of different solutions was adopted for different countries and integrated into a common development framework. Although the publication of lexicographic resources to implement spelling reforms has always been done for Portuguese, VOC represents a paradigm change, switching from idiosyncratic, closed source, paper-format official resources to standardized, open, free, web-accessible and reusable ones. We start by outlining the context that justifies the resource development and its requirements, then focusing on the description of the methodology, workflow and tools used, showing how a collaborative project in a common web-based platform and administration interface make the creation of such a long-sought and ambitious project possible.
Impairment in social communication skills is one of the core deficits in the children with Autism Spectrum Disorder (ASD). These children are characterized by an inherent inability to express their affective states thereby imposing limitations on traditional self-report and observational methodologies. However physiological signals are continuously available and are arguably not impacted by these difficulties. In recent years several assistive technologies utilizing the benefits of physiology-based systems have been investigated to promote social communication skills in this population. Among these we chose Virtual Reality (VR) as our platform. Investigations in the area of Human Computer Interaction (HCI) have shown that variations in the physiological signals can be evoked by different amounts of presence in the VR environment and the transition from one affective state to another is accompanied by dynamic shift in indicators of Autonomic Nervous System (ANS) activity. The presented work seeks to fuse behavioral viewing pattern and peripheral physiological features with the affective rating. Thus, this is a step towards indicating the potential of such a system to build an intelligent therapist-like affect-recognizer. The preliminary findings of a usability study are promising.
Syntax-based translation models that operate on the output of a source-language parser have been shown to perform better if allowed to choose from a set of possible parses. In this paper, we investigate whether this is because it allows the translation stage to overcome parser errors or to override the syntactic structure itself. We find that it is primarily the latter, but that under the right conditions, the translation stage does correct parser errors, improving parsing accuracy on the Chinese Treebank. 1
Lexicography in the Arab world has had important effects on the development of the Arabic language. The origin and subsequent development and refinement of traditional Arabic grammatical theory—as early as the eighth century- had intimate links with the practice of writing dictionaries. The Kitab al-ʿayn, by al-Khalil ibn Ahmad (d.c.786), which is the first full-scale dictionary in the Arab world, marked a significant milestone in the history of grammatical thought and set the tone for more works on Arabic grammar. For many centuries, the general mode of the theory has acknowledged a "closed" corpus of Qur'anic diction and pre-Islamic poetry and prose as the major source of Arabic lexicographic works. The main credo is that Arabic dictionaries should contain the "unattained" forms of the language and remain impervious to external persuasions; namely colloquialisms, borrowings, neologisms, and coinages. Arabic dictionaries continued to resist the slightest reform as to the codification of lexical innovations and the treatment of lexical gaps exhausting themselves to the point of stagnation. Today, English-Arabic dictionary editors have to deal with a huge number of lexical gaps that have cumulated over time. The lexical gap-filling process is carried out in a very unsystematic way that is far from creating an atmosphere of cooperation that ultimately contributes to creating unified English-Arabic lexical databases for lexicographic purposes. The paper explains how a modern English-Arabic dictionary can fall short in its modernizing role, and gives a snapshot of the most salient microstructural issues that characterize the Al-Mawrid Al-Hadeeth: A Modern English-Arabic Dictionary (2010).
When a video of someone speaking is paused, the stationary image of the speaker typically appears less flattering than the video, which contained motion. We call this the frozen face effect (FFE). Here we report six experiments intended to quantify this effect and determine its cause. In Experiment 1, video clips of people speaking in naturalistic settings as well as all of the static frames that composed each video were presented, and subjects rated how flattering each stimulus was. The videos were rated to be significantly more flattering than the static images, confirming the FFE. In Experiment 2, videos and static images were inverted, and the videos were again rated as more flattering than the static images. In Experiment 3, a discrimination task measured recognition of the static images that composed each video. Recognition did not correlate with flattery ratings, suggesting that the FFE is not due to better memory for particularly distinct images. In Experiment 4, flattery ratings for groups of static images were compared with those for videos and static images. Ratings for the video stimuli were higher than those for either the group or individual static stimuli, suggesting that the amount of information available is not what produces the FFE. In Experiment 5, videos were presented under four conditions: forward motion, inverted forward motion, reversed motion, and scrambled frame sequence. Flattery ratings for the scrambled videos were significantly lower than those for the other three conditions. In Experiment 6, as in Experiment 2, inverted videos and static images were compared with upright ones, and the response measure was changed to perceived attractiveness. Videos were rated as more attractive than the static images for both upright and inverted stimuli. Overall, the results suggest that the FFE requires continuous, natural motion of faces, is not sensitive to inversion, and is not due to a memory effect.
We consider a specific class of tree structures that can represent basic structures in linguistics and computer science such as XML documents, parse trees, and treebanks, namely, finite node-labeled sibling-ordered trees. We present axiomatizations of the monadic second-order logic (MSO), monadic transitive closure logic (FO(TC1)) and monadic least fixed-point logic (FO(LFP1)) theories of this class of structures. These logics can express important properties such as reachability. Using model-theoretic techniques, we show by a uniform argument that these axiomatizations are complete, i.e., each formula that is valid on all finite trees is provable using our axioms. As a backdrop to our positive results, on arbitrary structures, the logics that we study are known to be non-recursively axiomatizable.
Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. One of the most popular web personalization systems is recommender systems. In recommender systems choosing user information that can be used to profile users is very crucial for user profiling. In Web 2.0, one facility that can help users organize Web resources of their interest is user tagging systems. Exploring user tagging behavior provides a promising way for understanding users’ information needs since tags are given directly by users. However, free and relatively uncontrolled vocabulary makes the user self-defined tags lack of standardization and semantic ambiguity. Also, the relationships among tags need to be explored since there are rich relationships among tags which could provide valuable information for us to better understand users. In this paper, we propose a novel approach for learning tag ontology based on the widely used lexical database WordNet for capturing the semantics and the structural relationships of tags. We present personalization strategies to disambiguate the semantics of tags by combining the opinion of WordNet lexicographers and users’ tagging behavior together. To personalize further, clustering of users is performed to generate a more accurate ontology for a particular group of users. In order to evaluate the usefulness of the tag ontology, we use the tag ontology in a pilot tag recommendation experiment for improving the recommendation performance by exploiting the semantic information in the tag ontology. The initial result shows that the personalized information has improved the accuracy of the tag recommendation.
This paper presents the results of a set of preliminary experiments combining two knowledge-based partial dependency analyzers with two statistical parsers, applied to the Basque Dependency Treebank. The general idea will be to apply a stacked scheme where the output of the rule-based partial parsers will be given as input to MaltParser and MST, two state of the art statistical parsers. The results show a modest improvement over the baseline, although they also present interesting lines for further research.
Previous joint models of Chinese part-of-speech (POS) tagging and dependency parsing are extended from either graph- or transition-based dependency models. Our analysis shows that the two models have different error distributions. In addition, integration of graph- and transition-based dependency parsers by stacked learning (stacking) has achieved significant improvements. These motivate us to study the problem of stacking graph- and transition-based joint models. We conduct experiments on Chinese Penn Treebank 5.1 (CTB5.1). The results demonstrate that the guided transition-based joint model obtains better performance than the guided graph-based joint model. Further, we introduce a constituent-based joint model which derives the POS tag sequence and dependency tree from the output of PCFG parsers, and then integrate it into the guided transition-based joint model. Finally, we achieve the best performance on CTB5.1, 94.95 % in tagging accuracy and 83.98 % in parsing accuracy respectively.
It is well known that accuracies of statistical parsers trained over Penn treebank on test sets drawn from the same corpus tend to be overestimates of their actual parsing performance. This gives rise to the need for evaluation of parsing performance on corpora from different domains. Evaluating multiple parsers on test sets from different domains can give a detailed picture about the relative strengths/weaknesses of different parsing approaches. Such information is also necessary to guide choice of parser in applications such as machine translation where text from multiple domains needs to be handled. In this paper, we report a benchmarking study of different state-of-art parsers for English, both constituency and dependency. The constituency parser output is converted into CoNLL-style dependency trees so that parsing performance can be compared across formalisms. Specifically, we train rerankers for Berkeley and Stanford parsers to study the usefulness of reranking for handling texts from different domains. The results of our experiments lead to interesting insights about the out-of-domain performance of different English parsers.
BACKGROUND: This study examines inequalities in health in Laos. Because perception of health might affect ratings, we used both a global and a relative self-rated health (SRH) question. METHODS: The study was based on the fourth Lao Expenditure and Consumption Survey, 2007-2008. The study population consisted of 24 162 individuals 20 years or older. Two single-question measures of SRH were used: a global with no reference point and a relative with age group reference. RESULTS: Significant associations were found with age, sex, illiteracy, ethnicity, remote location, health measures, nutrition, and household poverty. Worse health was reported using SRH questions with reference points by the young rather than the old. CONCLUSION: In Laos, poor SRH is associated with illiteracy, inaccessibility, Mon-Khmer ethnicity, age, being a woman, and being poor. More factors were found to be associated with global rather than relative SRH.
Sentence realization, as one of the important components in natural language generation, has taken a statistical swing in recent years. While most previous approaches make heavy usage of lexical information in terms of N-gram language models, we propose a novel method based on unlexicalized tree linearization grammars. We formally define the grammar representation and demonstrate learning from either treebanks with gold-standard annotations, or automatically parsed corpora. For the testing phase, we present a linear time deterministic algorithm to obtain the 1-best word order and further extend it to perform exact search for n-best linearizations. We carry out experiments on various languages and report state-of-the-art performance. In addition, we discuss the advantages of our method on both empirical aspects and its linguistic interpretability.