Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
16504 papers
Compared to well-resourced languages such as English and Dutch, natural language processing (NLP) tools for Afrikaans are still not abundant. In the context of the AfriBooms project, KU Leuven and the North-West University collaborated to develop a first, small treebank, a dependency parser, and an easy to use online linguistic search engine for Afrikaans for use by researchers and students in the humanities and social sciences. The search tool is based on a similar development for Dutch, i.e. GrETEL, a user-friendly search engine which allows users to query a treebank by means of a natural language example instead of a formal search instruction.
BACKGROUND: The intraoperative application of focused transthoracic echocardiography (TTE) is often considered to be restricted. Echocardiography with pocket-sized hand held ultrasound systems has been shown to be feasible in various settings. OBJECTIVE: The aim of this study was to investigate the feasibility of the intraoperative application of pocket-sized echocardiography and the comparison of its imaging quality and diagnostic reliability and variability with a standard ultrasound system. METHODS: After written informed consent, TTE was performed on 40 anaesthetised general, vascular, visceral, thoracic surgical and orthopaedic patients according to the FATE protocol: first, with a pocket-sized and second, with a high-end ultrasound system randomly by two anaesthetists. Imaging quality of four basic and three additional FATE views was rated on an established scale from 1 (impossible) to 5 (perfect). Successful TTE was defined, if one basic FATE views would be rated as grade 4 or 5 or alternatively two views as grade 3. Pathologic findings by both ultrasound devices were documented and imaging quality and pathologic findings were compared. RESULTS: All 40 patients presented acceptable imaging quality, resulting in a success rate of 1.0 (97.5%-CI 0.91-1, p= 0.015). The individual imaging ratings of each view were significantly lower with the pocket-sized system, but still showed acceptable imaging quality. With the high-end device more pathologic findings were detected (107 vs. 87), but none of the relevant or severe pathologies were overseen with the hand-held device. CONCLUSION: The application of a pocket-sized echocardiography device for focused intraoperative TTE is feasible and can appropriate be used for the initial evaluation of relevant pathologies in the operating theatre.
OBJECTIVE: Examine the production of abstract and concrete nouns in patients with neurodegenerative disease using the Cookie Theft picture description. BACKGROUND: In a previous study, we observed a double dissociation in abstract and concrete word knowledge between the semantic variant of primary progressive aphasia (svPPA) and the behavioral variant of frontotemporal dementia (bvFTD). Compared to age-matched healthy controls, bvFTD patients were significantly more impaired for abstract nouns than for concrete nouns, and their poor abstract knowledge related to atrophy in the inferior frontal gyrus. In contrast, svPPA patients were significantly more impaired for concrete nouns compared to abstract nouns, associated with atrophy to the left temporal lobe. In this study, we test if the same neural regions that are critical for effective abstract and concrete word comprehension also play a role in the production of abstract and concrete words. DESIGN/METHODS: We assess the production of abstract and concrete nouns in 42 bvFTD and 21 svPPA patients using an oral description of the Cookie Theft picture. Patients met published diagnostic criteria, and concreteness or abstractness of each word was calculated using Brysbaert concreteness ratings (Brysbaert, Warriner & Kuperman, 2014). RESULTS: We observe the same double dissociation pattern during production as we previously saw with comprehension: bvFTD patients produce a smaller proportion of abstract nouns than svPPA patients. Moreover, the average concreteness rating for all nouns produced by svPPA patients is lower than for bvFTD. Regression analyses demonstrated that decreased abstract noun production in bvFTD relates to atrophy in the left inferior frontal gyrus. In addition, decreased concrete noun production in svPPA relates to atrophy in the left inferior temporal lobe. CONCLUSIONS: These results corroborate the finding that abstract and concrete nouns are represented in partially dissociable anatomic regions.
Con el desarrollo de la informática, en la investigación del lenguaje se introdujo la teoría y metodología de redes complejas, que transforma el sistema de la lengua en las redes complejas compuestas de nodos y enlaces para hacer un análisis cuantitativo de la estructura de la lengua. El desarrollo de la gramática de dependencias proporciona un apoyo teórico a la construcción del corpus anotado (treebank), por lo que el análisis estadístico con las redes complejas se hace posible. Este artículo presenta la teoría y metodología de las redes complejas y construye las redes sintácticas de dependencia a base del corpus anotado (treebank) de las expresiones orales del examen EEE-4 (Examen del Español como Especialidad - Nivel 4). Mediante el análisis de las características generales de las redes, incluyendo el número de nodos, los enlaces, el grado medio, la longitud media de los caminos, la distribución de grados y la centralización, tiene como objetivo descubrir la diferencia y similitud potencial entre las expresiones orales de distintos niveles. Además, con el análisis de conglomerados, esta investigación pretende demostrar la capacidad discriminatoria de las variables de las redes complejas y proporcionar una referencia potencial para el trabajo de calificación.
Discourse connectives (e.g. however, because) are terms that can explicitly convey a discourse relation within a text. While discourse connectives have been shown to be an effective clue to automatically identify discourse relations, they are not always used to convey such relations, thus they should first be disambiguated between discourse-usage non-discourse-usage. In this paper, we investigate the applicability of features proposed for the disambiguation of English discourse connectives for French. Our results with the French Discourse Treebank (FDTB) show that syntactic and lexical features developed for English texts are as effective for French and allow the disambiguation of French discourse connectives with an accuracy of 94.2%.
Facial expressions are one of the most important types of non-verbal communication. Although interpretation of facial expressions is usually robust, studies have shown that both age-related and disease-related factors can influence recognition accuracy. In particular, older people show deficits in recognition of negative expressions. Similarly, patients suffering from Parkinson's disease (PD) also show impairments in recognition of fear, anger, and disgust expressions. These studies so far have only focused on the basic, or "universal" expressions. Here, we were interested in investigating and comparing the effects of age and disease on facial expression processing for a wider range of both emotional and communicational expressions. For our ongoing study we recruited a total of 79 participants: 20 PD patients, 15 age-matched, older healthy controls (HC), and 44 younger healthy controls (HCS). During the experiment, participants were instructed to watch videos of 27 facial expressions performed by 6 different actors and to rate each expression based on 12 evaluative dimensions (arousal, valence, naturalness, politeness, persuasiveness, dynamic, familiarity, empathy, honesty, attractiveness, intelligence, and outgoingness) using a 7-point Likert scale. Ratings were analyzed using within-group and across-group correlations, factor analysis, and item analyses. Overall, we found that ratings of expressions were more different due to age, than due to disease-prevalence: r(PD/HC)=.756 versus r(PD/HCS)=.627, r(HC/HCS)=.640. Three out of six factors in the factor analysis were common for all groups (arousal-dynamic, familiarity-empathy, and naturalness-sincerity), showing common evaluation patterns. Confirming earlier findings of a "positivity effect", valence ratings of negative expressions were higher for both older groups (although valence ratings highly correlated within-group: all r>.919). Similarly, negative expression were perceived as more natural but less persuasive by both older groups. Overall, our results show that age-related factors play a much larger role than PD-related factors in processing of both emotional and communicational facial expressions. Meeting abstract presented at VSS 2016
This paper aims at filling the gap between the accuracy of Italian and English constituency parsing: firstly, we adapt the Bllip parser, i.e., the most accurate constituency parser for English, also known as Charniak parser, for Italian and trained it on the Turin University Treebank (TUT). Secondly, we design a parse reranker based on Support Vector Machines using tree kernels, where the latter can effectively generalize syntactic patterns, requiring little training data for training the model. We show that our approach outperforms the state of the art achieved by the Berkeley parser, improving it from 84.54 to 86.81 in labeled F1.
In this paper, the importance of “culture” is focused on regarding its relation to second/foreign language acquisition/learning. By reinterpreting the Iceberg Model of Culture, the author thinks that second/foreign language learners are exposed to the dominant culture with its social and linguistic norms and therefore they experience deculturalization, which also brings about the issue of the Self and the Other. It is suggested in the paper that a shift from communicative competence (CC) to intercultural communicative competence (ICC) in multicultural second/foreign language classes per se could enhance language learning by involving these learners’ native culture elements in the language learning/teaching process. While the paper illustrates some pedagogical implications that such a shift could entail, it concludes that introducing these practices in multicultural second/foreign language classes have the potential to enable both practitioners and learners to deal with power relations and the deculturalizing forces, which might be prevalent in such classes.
We tackle the challenge of learning part-of-speech classified translations as part of an inversion transduction grammar, by learning translations for English words with known part-of-speech tags, both from existing translation lexica and from parallel corpora. When translating from a low resource language into English, we can expect to have rich resources for English, such as treebanks, and small amounts of bilingual resources, such as translation lexica and parallel corpora. We solve the problem of integrating these heterogeneous resources into a single model using stochastic Inversion Transduction Grammars, which we augment with wildcards to handle unknown translations.
Facial expressions frequently involve multiple individual facial actions. How do facial actions combine to create emotionally meaningful expressions? Infants produce positive and negative facial expressions at a range of intensities. It may be that a given facial action can index the intensity of both positive (smiles) and negative (cry-face) expressions. Objective, automated measurements of facial action intensity were paired with continuous ratings of emotional valence to investigate this possibility. Degree of eye constriction (the Duchenne marker) and mouth opening were each uniquely associated with smile intensity and, independently, with cry-face intensity. In addition, degree of eye constriction and mouth opening were each unique predictors of emotion valence ratings. Eye constriction and mouth opening index the intensity of both positive and negative infant facial expressions, suggesting parsimony in the early communication of emotion.
The study examined the relationship between idiom familiarity, knowledge of idiom meaning and idiom transparency judgments in L2. A group of 23 intermediate Japanese learners of English were asked to provide familiarity ratings, transparency judgments, and definitions for 30 English idioms, 27 of which had semantically equivalent but compositionally different idiomatic counterparts in Japanese and 3 phrases for which semantic equivalents in L1 also shared the same structural properties. Transparency ratings were repeated after the instructional treatment. A comparison of pre-treatment and post-treatment transparency scores showed that knowledge of conventional idiom meanings had a strong effect on the learners’ perceptions of idiom transparency. Transparency judgments, however, were not found to be a reliable predictor of the learners’ ability to infer figurative meanings of the idiomatic phrases. Idiom familiarity was not found to have a significant effect on idiom comprehension or on transparency judgments either. A limited positive effect of language transfer on L2 idiom comprehension and transparency ratings was observed.
Semantic lexical similarity and relatedness are important issues in natural language processing (NLP). Similarity and relatedness are not the same, while they are very closely related. To date, in many works these two issues are mixed up which harm system’s effectiveness. A popular approach to measure semantic similarity and relatedness is utilizing WordNet, a lexical database. This paper shows that Wordnet’s gloss is a potential source for measuring semantic relatedness. Experiment result using WordSim353 relatedness database confirms the effectiveness of the approach.
The aim of the current study was to investigate if Openness – to – Experience and Neuroticism personality traits are associated with curiosity. This will help us to estimate whether knowledge expansion is dependent on a person’s personality and which trait is more willing to invest time on learning. The experiment consisted of two different sessions. To estimate curiosity, 40 subjects first performed a word-synonymy task, where Shannon’s (1948) entropy was estimated and the result of which lead to the measurement of uncertainty. Then in a second session, participants had the option to request for feedback between a few alternative options at a cost (time), and they were also required to estimate their satisfaction about the answer on a valence rating scale. Finally, participants were screened for personality traits. Neurotic individuals appeared to be more willing in investing time on feedback request, in contrast to open individuals.
Due to the constant increasing of electronic textual information, modern society needs for the automatic processing of natural language (NL). The main purpose of NL automatic text processing systems is to analyze and create texts and represent their content. The purpose of the paper is the development of linguistic and software bases of an automatic system for processing English publicistic texts. This article discusses the examples of different approaches to the creation of linguistic databases for processing systems. The author gives a detailed description of basic building blocks for a new linguistic processor: lexicalsemantic, syntactical and semantic-syntactical. The main advantage of the processor is using special semantic codes in the alphabetical dictionary. The semantic codes have been developed in accordance with a lexical-semantic classification. It helps to precisely define semantic functions of the keywords that are situated in parsing groups and allows the automatic system to avoid typical mistakes. The author also represents the realization of a developed linguistic database in the form of a training computer program.
The paper compares the grammar handbook <i>Gyakorlati Ilir Nyelvtan</i> (Baja, 1874, <sup>2</sup>1881) by Mihálovics with Mažuranić's <i>Slovnica Hèrvatska</i> (<sup>4</sup>1869), as Mažuranić is mentioned in the foreword as the normative model used in the handbook. This comparison will include their terminology, purpose, structure, and normative prescription, and will determine in which cases Mihálovics follows Mažuranić’s grammar and in which he distances himself from it. Since the grammar handbook was published outside the Croatian (ethnic and linguistic) area, the paper will show to what extent the characteristics of the Croatian linguistic norm were preserved in the Hungarian part of the Danube Region in the late 19<sup>th</sup> century.
This volume takes as its central organizing principle the foundational understanding about community knowledge that challenges “narrow conceptions of language, literacy, personal stories, bounded or contained learning contexts (e.g., home, community, schools), hegemonic cultural and linguistic norms, quantitative and static views of ‘resources,’ and limited attention to the agency, identities, and strategic actions of diverse students and their families as they traverse contexts” (daSilva Iddings, this volume). The touchstone to this approach is “Funds of Knowledge” as it has been conceptualized for nearly twenty-five years. This chapter will briefly summarize the approach as it has evolved and will lay out the programmatic implementation as it unfolded within CREATE.
In recent years there has been a lot of interest in cross-lingual parsing for developing treebanks for languages with small or no annotated treebanks. In this paper, we explore the development of a cross-lingual transfer parser from Hindi to Bengali using a Hindi parser and a Hindi-Bengali parallel corpus. A parser is trained and applied to the Hindi sentences of the parallel corpus and the parse trees are projected to construct probable parse trees of the corresponding Bengali sentences. Only about 14% of these trees are complete (transferred trees contain all the target sentence words) and they are used to construct a Bengali parser. We relax the criteria of completeness to consider well-formed trees (43% of the trees) leading to an improvement. We note that the words often do not have a one-to-one mapping in the two languages but considering sentences at the chunk-level results in better correspondence between the two languages. Based on this we present a method to use chunking as a preprocessing step and do the transfer on the chunk trees. We find that about 72% of the projected parse trees of Bengali are now well-formed. The resultant parser achieves significant improvement in both Unlabeled Attachment Score (UAS) as well as Labeled Attachment Score (LAS) over the baseline word-level transferred parser.
This paper presents a novel high-order dependency parsing framework that targets non-projective treebanks. It imitates how a human parses sentences in an intuitive way. At every step of the parse, it determines which word is the easiest to process among all the remaining words, identifies its head word and then folds it under the head word. Further, this work is flexible enough to be augmented with other parsing techniques.
espanolCon el desarrollo de la informatica, en la investigacion del lenguaje se introdujo la teoria y metodologia de redes complejas, que transforma el sistema de la lengua en las redes complejas compuestas de nodos y enlaces para hacer un analisis cuantitativo de la estructura de la lengua. El desarrollo de la gramatica de dependencias proporciona un apoyo teorico a la construccion del corpus anotado (treebank), por lo que el analisis estadistico con las redes complejas se hace posible. Este articulo presenta la teoria y metodologia de las redes complejas y construye las redes sintacticas de dependencia a base del corpus anotado (treebank) de las expresiones orales del examen EEE-4 (Examen del Espanol como Especialidad - Nivel 4). Mediante el analisis de las caracteristicas generales de las redes, incluyendo el numero de nodos, los enlaces, el grado medio, la longitud media de los caminos, la distribucion de grados y la centralizacion, tiene como objetivo descubrir la diferencia y similitud potencial entre las expresiones orales de distintos niveles. Ademas, con el analisis de conglomerados, esta investigacion pretende demostrar la capacidad discriminatoria de las variables de las redes complejas y proporcionar una referencia potencial para el trabajo de calificacion. EnglishWith the development of information technology, the theory and methodology of complex network has been introduced to the language research, which transforms the system of language in a complex networks composed of nodes and edges for the quantitative analysis about the language structure. The development of dependency grammar provides theoretical support for the construction of a treebank corpus, making possible a statistic analysis of complex networks. This paper introduces the theory and methodology of the complex network and builds dependency syntactic networks based on the treebank of speeches from the EEE-4 oral test. According to the analysis of the overall characteristics of the networks, including the number of edges, the number of the nodes, the average degree, the average path length, the network centrality and the degree distribution, it aims to find in the networks potential difference and similarity between various grades of speaking performance. Through clustering analysis, this research intends to prove the network parameters’ discriminating feature and provide potential reference for scoring speaking performance.
The article deals with the phenomenon of diglossia in the context of development of Greek language in the Hellenistic period, observes in diachrony the correlation between the linguistic norm of Atticism and Koine Greek – from the beginning of theory of Atticist mimesis to the times of second sophistry; determines the specificity of Koine Greek of the New Testament and its relation to, on the one hand, Atticism canon and literary Koine Greek, and on the other hand, – to the language of the early Patristic literature.
Dataset for TACL submission "The Galactic Dependencies Treebanks: Getting More Data by Synthesizing New Languages".<br> The scripts and model parameters for replicating this dataset are available at https://github.com/gdtreebank/gdtreebank.
Abstract Gender neutral language has been one of the most hotly debated issues in Bible translation in recent decades, especially in translations into English. The article presents some aspects of this problem expanding the perspective and comparing gender neutral language usage in modern translations of Scripture into English and Polish: the New International Version and the Paulist Bible and the Poznan Bible, with occasional references to other English and Polish translations. Renditions of selected New Testament terms such as anthrōpos, anēr, adelphos/adelphoi and huioi are examined, as well as English and Polish translations of diakoneo when it describes women accompanying Jesus in the synoptic gospels. Translations of “Junia/Junius” (Rom 16:7) are also compared as well as the issue of Phoebe the “deaconess” in Rom 16:1. The author concludes that solutions concerning gender neutral language in English and Polish translations of the Bible, sometimes similar, are not identical due to differences between these languages, due to different socio-linguistic norms characterizing Polish and English audiences respectively and due to the fact that the English translation is addressed to the evangelical Christians, while the Polish ones to the Catholics.
Universal Dependencies (UD) are gaining much attention of late for systematic evaluation of cross-lingual techniques for crosslingual dependency parsing. In this paper we present our work in line with UD. Our contribution to this is manifold. We extend UD to Indian languages through conversion of Pān inian Dependencies to UD for the Hindi Dependency Treebank (HDTB). We discuss the differences in annotation in both the schemes, present parsing experiments for both the formalisms and empirically evaluate their weaknesses and strengths for Hindi. We produce an automatically converted Hindi Treebank conforming to the international standard UD scheme, making it useful as a resource for multilingual language technology.
Nonostante una secolare tradizione lessicografica, la lingua latina manca ancora di risorse lessicali di tipo computazionale aggiornate allo stato dell’arte. Ciò è strettamente connesso alla limitata disponibilità di corpora testuali latini annotati linguisticamente, sulla cui base empirica possano essere costruite nuove risorse lessicali. Tuttavia, una serie di progetti mirati allo sviluppo di avanzate risorse linguistiche per il latino (tra cui alcune treebank) è stata avviata nel corso dell’ultimo decennio. In questo articolo, presentiamo Latin Vallex, un lessico di valenza per il latino realizzato in stretta connessione con l’annotazione semantico-pragmatica di due treebank latine comprensive di testi di epoche e generi diversi. Ciò consente di connettere biunivocamente le strutture valenziali registrate nel lessico e le loro occorrenze nei dati testuali delle treebank.
We describe results of investigation of a specific type of discontinuous constructions, namely non-projective constructions concerning verbs and their arguments. This topic is especially important for languages with a relatively free word order, such as Czech, which is the language we have primarily worked with. For comparison, we have included some results for English. The corpora used for both languages are the Prague Czech-English Dependency Treebank and the Prague Dependency Treebank, which are both annotated at a dependency syntax level as well as a deep (semantic) level, including verbs and their valency (arguments). We are using traditionally defined non-projectivity on trees with full linear ordering, but the two levels of annotation are innovatively combined to determine if a particular (deep) verb -argument structure is non-projective. As a result, we have identified several types of discontinuities, which we classify either by the verb class or structurally in terms of the verb, its arguments and their dependents. In addition, we have quantitatively compared selected phenomena found in Czech translated texts (in the PCEDT) to the native Czech as found in the original Prague Dependency Treebank.
Tokenizer, POS Tagger, Lemmatizer and Parser models for all 50 languages of Universal Depenencies 2.0 Treebanks, created solely using UD 2.0 data (http://hdl.handle.net/11234/1-1983). The model documentation including performance can be found at http://ufal.mff.cuni.cz/udpipe/users-manual#universal_dependencies_20_models. To use these models, you need UDPipe binary version at least 1.2, which you can download from http://ufal.mff.cuni.cz/udpipe. In addition to models itself, all additional data and value of hyperparameters used for training are available in the second archive, allowing reproducible training.
Nonostante una secolare tradizione lessicografica, la lingua latina manca ancora di risorse lessicali di tipo computazionale aggiornate allo stato dell’arte. Cio e strettamente connesso alla limitata disponibilita di corpora testuali latini annotati linguisticamente, sulla cui base empirica possano essere costruite nuove risorse lessicali. Tuttavia, una serie di progetti mirati allo sviluppo di avanzate risorse linguistiche per il latino (tra cui alcune treebank) e stata avviata nel corso dell’ultimo decennio. In questo articolo, presentiamo Latin Vallex, un lessico di valenza per il latino realizzato in stretta connessione con l’annotazione semantico-pragmatica di due treebank latine comprensive di testi di epoche e generi diversi. Cio consente di connettere biunivocamente le strutture valenziali registrate nel lessico e le loro occorrenze nei dati testuali delle treebank.
In this paper the systems submitted by the joint team of Dublin City University and National Taiwan University to the IALP 2016 Shared Task: Dimensional Sentiment Analysis for Chinese Words are presented. The systems learn the vector representation using Word2Vec algorithm for each Chinese word for sentiment analysis. The corpus used for the calculation of vector representation is 5 years (2006 to 2010) of the LDC Chinese Gigaword Fifth Edition corpus. The systems calculated similarities between a test Chinese word and each word in training corpus of the shared task with human annotation and took the valence-arousal ratings of the most similar words as the ratings of the test word. The performance of the submitted systems are around the same level of the shared task's baseline system. We will be looking at the performance gap with top-ranked systems in several aspects including corpus used for training and methodology.
The OPT submission to the Shared Task \nof the 2016 Conference on Natural Language \nLearning (CoNLL) implements a \n‘classic’ pipeline architecture, combining \nbinary classification of (candidate) explicit \nconnectives, heuristic rules for non-explicit \ndiscourse relations, ranking and ‘editing’ \nof syntactic constituents for argument identification, \nand an ensemble of classifiers to \nassign discourse senses. With an end-toend \nperformance of 27.77 F1 on the English \n‘blind’ test data, our system advances \nthe previous state of the art (Wang & Lan, \n2015) by close to four F1 points, with particularly \ngood results for the argument identification \nsub-tasks. OPT system results appear \nmore competitive on the new, ‘blind’ \ntest data than on the ‘test’ and ‘development’ \nsections of the Penn Discourse Treebank \n(PDTB; Prasad et al., 2008), which \nmay indicate reduced over-fitting to specific \nproperties of the venerableWall Street \nJournal (WSJ) text underlying the PDTB
We describe the Corpus of Spoken Icelandic (ÍS-TAL) which is made up of 15 hours of spontaneous naturally occurring conversa-tions, 31 conversations in all. The corpus comprises 184,080 tokens, 14,297 types and 9,221 lemmas. It has been transcribed using standard orthography. We present a list of the 30 most common lemmas in the corpus and compare it to a list of the most frequent lemmas in the written language, concluding that the differences between the two lists are smaller than expected. We have tagged the corpus morphologically with a statistical tagger that had been trained on written texts. The results are much better than we expected, and the tagging accuracy is as least as high as for the written texts. The final part of the paper is a report on a work in progress. We have been experimenting with converting the morphological tagging into a shallow syntactic markup by applying a few simple hand-written rules. Even though the analysis we get by using this procedure is bound to be incomplete and contain several errors, we conclude that the results are promising and we can use this method to build a simple yet useful treebank with minimal effort. 1.
108 Objectives To diagnose the dementia subtypes has significant information for determining the treatment strategies and predicting the clinical courses. Recently, many dementia patients undergo dopamine transporter (DAT) imaging, in addition to brain perfusion imaging to investigate the subtypes of dementia. However, patients must wait for tracer decay when using the conventional method, and this is burdensome for dementia patients and often delays the decision making for treatment. We developed a prototype CdTe SPECT system with 4-Pixel Matched Collimator for brain study. This system provides high energy resolution (6.6%), high sensitivity (220 cps/MBq/head) and provide high spatial resolution images of I-123 and Tc-99m simultaneously. The aim of this study was to evaluate findings and quantification on dual isotope study of cerebral blood flow (CBF) and Dopamine transporter (DAT) images with the new SPECT system. Methods We prospectively enrolled 21 patients with cognitive disorder. Every patient underwent imaging examinations on the same schedule. We used 3-head scanner (GCA-9300R, TOSHIBA) as a conventional scanner. Both 99mTc-ECD (CBF) and 123I-IFP (DAT) scans were independently performed with the conventional scanner on separate days, and simultaneously performed with the new system on another day. CBF and DAT images were both visually and quantitatively analyzed.For visual analyses, two nuclear medicine physicians visually interpreted both DAT and CBF images rating the severity into 4 grades (from 0 to 3). Totally 12 (6/hemisphere) supratentorial regions on the 99mTc-ECD images and 2 regions (left and right striatum) on the 123I-IFP were defined for each patient. The correlation of visual analysis results between GCA and SPICA was evaluated by weighted Kappa statistics. For quantitative analyses, we calculated the cerebrum-thalamus count ratio of 99mTc-ECD and the specific-to-background ratios of 123I-IFP. We assessed those regions of Pearson9s correlation coefficient and intraclass correlation coefficient (ICC) between the conventional scanner and the new system. Results The weighted Kappa statistics between GCA and SPICA were 0.67 and 0.68 for 99mTc-ECD and 123I-IFP, respectively, indicating high interrater reliability. The semi-quantitative analyses demonstrated that the 99mTc-ECD cerebrum-thalamus count ratio of SPICA was well correlated to GCA (R=0.81, p Conclusions The findings and quantitative results of both CBF and DAT images of dual isotope study with the new system had excellent correlation with those of single isotope studies with the conventional scanner with two separate days. In conclusion, our new SPECT scanner with semiconductor detectors enables quantitative dual tracer diagnostic imaging of CBF and Dopamine transporter imaging in patients with cognitive disorder. This technique may enable the one-stop imaging diagnosis for dementia and reduce the burden on patients.
During the first decade of this century, a new subculture emerged on the Runet (the Russian Internet). It promoted a version of the deliberately distorted Russian language, first of all by systematically altering orthographic and punctuation norms. This “padonkafskii” language (given the misspelled usage of the original word, it seems more accurate to translate it as “basterds,” as in in Tarantino’s movie) has been analyzed by linguists. Its political role and implicit message have not been scrutinized until now. In the article, Ilya Kukulin argues that this <i>basterd</i> language was used and promoted by pro-Kremlin political entrepreneurs to develop new strategies of communication: performances of cynical transgression and symbolic violence through the humiliation of counterparts. Cyberbullying became a distinctive style of seemingly nonconformist subculture, and already in this capacity was used by the regime. Central to this communication strategy was the cult of power, xenophobia, and discarding of any idealistic motivations of human behavior as hypocritical public relations technologies. At the same time, the <i>basterd</i> subculture itself claimed the status of nonconformist sincerity for its members. This image of a novel subculture helped to promote its aggressive xenophobia and support for the authorities among the most socially dynamic groups of Russia’s population. Political mobilization of the <i>basterds</i>’ language relied on the earlier aesthetic and political strategies of Russian mass culture of the 1990s, which were partially reconfigured or further developed. The radical and socially escapist irony underlying the cultural scene of the 1990s (the article uses Russian punk rock as an example) has been recast into the view of society as a total war, perceived from the position of total cynicism and nihilism. Cynicism has become the main mode of social thinking in modern Russia. Once popular with many bloggers, the <i>basterds</i>’ language is now out of vogue. Moreover, experiments with language transgressions seem to have lost their popularity. Instead, the role of transmitters of an ultra-cynical worldview and proponents of symbolic violence has been assumed by officialdom as represented by press secretaries of the president, key ministries, or MPs. They display the same conscious transgression of linguistic norm and moral standards as their <i>Basterd</i> predecessors, who pretended to be antiestablishment and nonconformist. The preponderance of <i>basterd</i> language during the previous decade cleared the ground for hate-speech and symbolic violence in the public sphere as an acceptable, attractive, and even necessary format of public communication.
Perirhinal cortex (PrC) has been implicated as a brain region in the medial temporal lobes (MTL) that critically contributes to familiarity-based recognition memory, a process that allows for recognition to occur independently of contextual recollection. Informed by neurophysiological research in non-human primates, fMRI, as well as behavioural work in humans, the current thesis research tests the novel hypothesis that PrC cortex functioning also underlies the ability to assess cumulative lifetime familiarity with object concepts that are characterized by a lifetime of experiences. In Chapter 2, a patient (NB) with a left anterior temporal lobe (ATL) lesion that included PrC as well as an amnesic patient (HC) with a bilateral lesion to the hippocampus were tested on their ability to make lifetime familiarity judgements for object concepts (i.e., concrete nouns). Patient NB made abnormal familiarity ratings for objects concepts relative to matched controls, while patient HC produced ratings that did not differ from control participants. In Chapter 3, I tested healthy young adults on a frequency judgement task and lifetime familiarity task while they underwent fMRI. A region in the left PrC tracked both the perceived frequency of recent laboratory exposure as well as perceived lifetime familiarity. Finally, in Chapter 4, I tested whether indeed lifetime familiarity judgements are based on conceptual processing by making use of an associative priming paradigm. Associatively-related primes increased the perceived familiarity of object concepts while also reducing the latency of these judgements. Overall, the results from all three empirical chapters provides evidence that warrants an extension of PrC functioning to include the cumulative assessment of lifetime familiarity with object concepts.
A known way to improve the accuracy of dependency parsers is to combine several different parsing algorithms, in such a way that the weaknesses of each of the models can be compensated by the strengths of others. For example, voting-based combination schemes are based on variants of the idea of analyzing each sentence with various parsers, and constructing a combined output where the head of each node is determined by “majority vote” among the different parsers. Typically, such approaches combine very different parsing models to take advan- tage of the variability in the parsing errors they make. In this paper, we show that consistent improvements in accuracy can be obtained in a much simpler way by combining a single parser with itself. In particular, we start with a greedy implementation of the Nivre pseudo-projective arc-eager algorithm, a well-known left-to-right transition-based parser, and we combine it with a “mirrored” version of the algorithm that analyzes sentences from right to left. To determine which of the two obtained outputs we trust for the head of each node, we use simple criteria based on the length and position of dependency arcs. Experiments on several datasets from the CoNLL-X shared task and the WSJ section of the English Penn Treebank show that the novel combination system obtains better performance than the baseline arc-eager parser in all cases. To test the generality of the approach, we also perform experiments with a different transition system (arc-standard) and a different search strategy (beam search), obtaining similar improvements in all these settings.
Recently, these has been a surge on studying how to obtain partially annotated data for model supervision. However, there still lacks a systematic study on how to train statistical models with partial annotation (PA). Taking dependency parsing as our case study, this paper describes and compares two straightforward approaches for three mainstream dependency parsers. The first approach is previously proposed to directly train a log-linear graph-based parser (LLGPar) with PA based on a forest-based objective. This work for the first time proposes the second approach to directly training a linear graph-based parse (LGPar) and a linear transition-based parser (LTPar) with PA based on the idea of constrained decoding. We conduct extensive experiments on Penn Treebank under three different settings for simulating PA, i.e., random dependencies, most uncertain dependencies, and dependencies with divergent outputs from the three parsers. The results show that LLGPar is most effective in learning from PA and LTPar lags behind the graph-based counterparts by large margin. Moreover, LGPar and LTPar can achieve best performance by using LLGPar to complete PA into full annotation (FA).
Most research on human fear conditioning and its generalization has focused on adults whereas only little is known about these processes in children. Direct comparisons between child and adult populations are needed to determine developmental risk markers of fear and anxiety. We compared 267 children and 285 adults in a differential fear conditioning paradigm and generalization test. Skin conductance responses (SCR) and ratings of valence and arousal were obtained to indicate fear learning. Both groups displayed robust and similar differential conditioning on subjective and physiological levels. However, children showed heightened fear generalization compared to adults as indexed by higher arousal ratings and SCR to the generalization stimuli. Results indicate overgeneralization of conditioned fear as a developmental correlate of fear learning. The developmental change from a shallow to a steeper generalization gradient is likely related to the maturation of brain structures that modulate efficient discrimination between danger and (ambiguous) safety cues.
Automatic metaphor detection usually relies on various features, incorporating e.g. selectional preference violations or concreteness ratings to detect metaphors in text. These features rely on background corpora, hand-coded rules or additional, manually created resources, all specific to the language the system is being used on. We present a novel approach to metaphor detection using a neural network in combination with word embeddings, a method that has already proven to yield promising results for other natural language processing tasks. We show that foregoing manual feature engineering by solely relying on word embeddings trained on large corpora produces comparable results to other systems, while removing the need for additional resources.
Hoarding is a complex and impairing psychiatric disorder and a public health problem. Traditionally it is assessed through observation and interview, but recently a new method has been proposed where living quarters of an individual are visually compared with a set of template images ranked according to the “Clutter Image Rating” (CIR) scale from 1 to 9. However, such an assessment is time-consuming, subjective, and weak in repeatability. We propose an automatic method for classifying hoarding images according to the CIR scale. Since clutter in living quarters (e.g., piles of boxes, newspapers, clothing) corresponds to “busy” areas with lots of edges in captured images, we use the histogram-of-gradients (HOG) descriptor to characterize images and estimate the CIR value using two methods: regression and classification. In 4-fold cross-validation on 620 images that we harvested from the internet, both methods result in mean-absolute CIR error of about 1.2. Given the simplicity of our method, this is an encouraging result as it approximates ratings by trained professionals who admit assigning CIR values within ± 1 CIR point.
Continuous word representations appeared to be a useful feature in many natural language processing tasks.Using fixed-dimension pre-trained word embeddings allows avoiding sparse bag-of-words representation and to train models with fewer parameters.In this paper, we use fixed pre-trained word embeddings as additional features for a neural scoring function in the MST parser.With the multi-layer architecture of the scoring function we can avoid handcrafting feature conjunctions.The continuous word representations on the input also allow us to reduce the number of lexical features, make the parser more robust to out-of-vocabulary words, and reduce the total number of parameters of the model.Although its accuracy stays below the state of the art, the model size is substantially smaller than with the standard features set.Moreover, it performs well for languages where only a smaller treebank is available and the results promise to be useful in cross-lingual parsing.
This article proposes an ontology design pattern for leading knowledge providers to represent knowledge in more normalized, precise and interrelated ways, hence in ways that help the matching and exploitation of knowledge from different sources. This pattern is a knowledge sharing best practice that is domain and language independent. It can be used as a criteria for measuring the quality of an ontology. This pattern is: using binary relation types directly derived from concept types, especially role types or types of process. The article explains and illustrates this pattern, and relates it to other patterns and general ontology quality criteria. It also provides an ontology for automatically deriving relation types from concept types (e.g., those from lexical ontologies such as those derived from the WordNet lexical database). This derivation helps normalizing knowledge, reduces having to introduce new relation types and helps keeping all the types organized.
In this paper, we investigate four important issues together for explicit discourse relation labelling in Chinese texts: (1) discourse connective extraction, (2) linking ambiguity resolution, (3) relation type disambiguation, and (4) argument boundary identification. In a pipelined Chinese discourse parser, we identify potential connective candidates by string matching, eliminate non-discourse usages from them with a binary classifier, resolve linking ambiguities among connective components by ranking, disambiguate relation types by a multiway classifier, and determine the argument boundaries by conditional random fields. The experiments on Chinese Discourse Treebank show that the F1 scores of 0.7506, 0.7693, 0.7458, and 0.3134 are achieved for discourse usage disambiguation, linking disambiguation, relation type disambiguation, and argument boundary identification, respectively, in a pipelined Chinese discourse parser.
We propose a method for improving the dependency parsing of complex sentences. This method assumes segmentation of input sentences into clauses and does not require to re-train a parser of one's choice. We represent a sentence clause structure using clause charts that provide a layer of embedding for each clause in the sentence. Then we formulate a parsing strategy as a two-stage process where (i) coordinated and subordinated clauses of the sentence are parsed separately with respect to the sentence clause chart and (ii) their dependency trees become subtrees of the final tree of the sentence. The object language is Czech and the parser used is a maximum spanning tree parser trained on the Prague Dependency Treebank. We have achieved an average 0.97% improvement in the unlabeled attachment score. Although the method has been designed for the dependency parsing of Czech, it is useful for other parsing techniques and languages.
It is now widely acknowledged that, between the fifteenth and the seventeenth centuries, most of the European national grammatical traditions were derived from the long-established Graeco-Latin descriptive and normative framework. However, a thorough investigation into the particulars of such a ‘transfer’, at a time when the first grammars of the English vernacular were progressively translated from the Latin, or written directly in English, is still to be carried out. How were classical linguistic norms practically transferred to English? How was usage then looked upon? Why was it decided that the vernacular should be taught? In this paper, I will examine in some detail how the first English grammarians integrated the vernacular of England into the paradigm of Latin grammar. We shall also study the conditions under which the specificities of English were revealed. But our main concern will be to try and determine whether any challenging position to the prevalent model that had sprung from the Graeco-Roman tradition can be traced back. If this long-established tradition appeared at that time as the only one apt to guarantee the efficiency of grammatical description, it seems that it was consistently challenged even by the most prominent figures.
We describe a simple but effective method for cross-lingual syntactic transfer of dependency parsers, in the scenario where a large amount of translation data is not available. The method makes use of three steps: 1) a method for deriving cross-lingual word clusters, which can then be used in a multilingual parser; 2) a method for transferring lexical information from a target language to source language treebanks; 3) a method for integrating these steps with the density-driven annotation projection method of Rasooli and Collins (2015). Experiments show improvements over the state-of-the-art in several languages used in previous work, in a setting where the only source of translation data is the Bible, a considerably smaller corpus than the Europarl corpus used in previous work. Results using the Europarl corpus as a source of translation data show additional improvements over the results of Rasooli and Collins (2015). We conclude with results on 38 datasets from the Universal Dependencies corpora.