Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
18265 papers
Functional Combinatory Categorial Grammar (FCCG) advances the field of combi- natory categorial grammars by enabling semantic dependencies to be determined directly from the syntactic derivation under the action of a small set of extraction rules. Pred- icates are extracted composably and can be used to apply semantic constraints during parsing. The approach is an alternative to that of classical CCG which requires (i) map- ping from categories to lambda expressions, (ii) a set of semantic transformation rules for unary combination, and (iii) an explicit �-reduction stage. GFCCG, a generalised form of the grammar, has previously been applied to situation assessment (McMichael, Jarrad, & Williams, 2006). In FCCG, combinators are largely distinguished by their semantic purpose. Unary combination is only used for preterminal-terminal transitions. Replacing unary type- raising and type-changing by their binary counterparts R and P tends to reduce parse ambiguity. Four other binary combinators are introduced to model various semantic phenomena: functional composition (F), modification (M), apposition (A) and copular modification (Q). Of the combinators of classical CCG, only binary coordination (&) is retained. The category is the natural feature structure for CCG, and we show how it may be extended to host semantic and parsing-related features compactly. The grammar is demon- strated by extracting an FCCG-annotated corpus from the Penn treebank using the com- binator calculator described in (Foreman & McMichael, 2004). Only fifty categories and 140 productions cover 99.7% of the extracted corpus, a substantially more efficient repre- sentation than previous conversions. We adopt a factored conditional statistical model, and provide an efficient iterative learning algorithm involving direct feedback of parsing errors that does not require enu- meration of the parse forest. While the best parser performances on data derived from the Penn treebank have come from fully lexicalized parsers, we have been motivated by the need to provide good coverage outside that relatively narrow training domain. We have therefore used a semilexicalised feature model, which does not, for example, contain bilexicalised features. Spurious ambiguity is controlled via probabilistic scoring coupled with agenda-based A* parsing. The parser uses an auxiliary queue prioritized by multi-tag probabilities for terminal node introduction. The parser's syntactic dependency F-score of 79.2% compares well with the best labelled syntactic dependency F-score for a fully lexicalised CCG parser tested on data consistent with the training domain of 84.6% (Clark & Curran, 2004b). The parser obtained a semantic extraction F-score of 83.1%.
Group identifications and intergroup relations among Turkish Dutch respondents What determines group identification processes among ethnic minority groups and how are these processes related to in-group and out-group evaluations? This article focuses on Turkish and Dutch identification among Turkish Dutch respondents and their feelings towards different ethnic and religious groups. The results show that Turkish identification is strong and Dutch identification rather weak, and that both group identifications are not strongly associated. Perceived socio-structural characteristics of intergroup relations (stability, legitimacy, permeability, and discrimination) affected both Turkish and Dutch identification. Group identification was positively related to (ethnic and religious) in-group evaluation, but there were few relationships with out-group evaluations. The affective ratings of Moroccans, Antilleans, Jews and non-believers were quite negative.
The present paper proposes a method by which to translate outputs of a robust HPSG parser into semantic representations of Typed Dynamic Logic (TDL), a dynamic plural semantics defined in typed lambda calculus. With its higher-order representations of contexts, TDL analyzes and describes the inherently inter-sentential nature of quantification and anaphora in a strictly lexicalized and compositional manner. The present study shows that the proposed translation method successfully combines robustness and descriptive adequacy of contemporary semantics. The present implementation achieves high coverage, approximately 90%, for the real text of the Penn Treebank corpus.
Multilingual dependency parsing is gaining popularity in recent years for several reasons. Dependency structures are more adequate for languages with freer word order than the traditional constituency notion. There is a growing availability of dependency treebanks for new languages. Broad coverage statistical dependency parsers are available and easily portable to new languages. Dependency parsing can provide useful contributions in areas such as information extraction, machine translation and question answering, among others. In addition, syntactic head-dependent pairs are a good interface between the traditional phrase structures and semantic theta roles. In this paper we present the learning curves of a statistical dependency parser for four languages: Arabic, Bulgarian, Italian and Slovene. We discuss issues that mostly concern the employed annotation scheme for each treebank with an emphasis on coordinated structures. Povzetek: Opisano je večjezično odvisnostno skladenjsko razčlenjevanje štirih jezikov. 1
We introduce MaltParser, a data-driven parser generator for dependency parsing. Given a treebank in dependency format, MaltParser can be used to induce a parser for the language of the treebank. MaltParser supports several parsing algorithms and learning algorithms, and allows user-defined feature models, consisting of arbitrary combinations of lexical features, part-of-speech features and dependency features. MaltParser is freely available for research and educational purposes and has been evaluated empirically on Swedish, English, Czech, Danish and Bulgarian. 1.
Literature suggests that relatively simple stimuli such as emotional facial expressions elicit neural activation in subcortical-limbic regions whereas contextually richer emotional pictures generate activation in a broader network of prefrontal as well as subcortical-limbic regions. The extent to which contextual features modulate subjective and neural responses associated with responses to emotional faces is unclear. Normative valence and arousal ratings for a large corpus of affective pictures (IAPS) were reviewed to explore whether emotional pictures containing both faces and context evoked more intense subjective emotional reactions than faces presented alone. This review study demonstrated that subjective emotional reactions to emotional faces with contextual information were greater than those to faces. An fMRI study was conducted to examine neural reactivity to these two types of emotional stimuli. Eleven healthy right-handed subjects viewed passively emotional stimuli during event-related functional magnetic resonance imaging (fMRI) assessment. Emotional faces augmented by contextual information elicited significant brain activity in the prefrontal cortex (BA10/11/47) as well as amygdala and thalamus. In contrast, emotional facial expressions provoked neural responses only in the subcortical-limbic/paralimbic regions including amygdala, thalamus, insula and posterior cingulate gyrus. These findings suggest that there are different but overlapping brain networks engaged by emotional faces and faces augmented by contextual information. The amygdala and thalamus can be regarded as common regions associated with emotional processing. Prefrontal regions may be unique in more cognitive and conscious processing of emotional faces augmented by contextual information.
Automatic analysis of syntax is one of the core problems in natural language processing. Despite significant advances in syntactic parsing of written text, the application of these techniques to spontaneous spoken language has received more limited attention. The recent explosive growth of online, accessible corpora of spoken language interactions opens up new opportunities for the development of high accuracy parsing approaches to the analysis of spoken language. The availability of high accuracy parsers will in turn provide a platform for development of a wide range of new applications, as well as for advanced research on the nature of conversational interactions. One concrete field of investigation that is ripe for the application of such parsing tools is the study of child language acquisition. In this thesis, we describe an approach for analyzing the syntactic structure of spontaneous conversational language in parent-child interactions. Specific emphasis is placed on the challenge of accurately annotating the English corpora in the CHILDES database with grammatical relations (such as subject, objects and adjuncts) that are of particular interest and utility, to researchers in child language acquisition. This work involves rule-based and corpus-based natural language processing techniques, as well as methodology for combining results from different parsing approaches. We present novel strategies for integrating the results of different parsers into a system with improved accuracy. One practical application of this research is the automation of language competence measures used by clinicians and researchers of child language development. We present an implementation of an automatic version of one such measurement scheme. This provides not only a useful tool for the child language research community, but also a task-based evaluation framework for grammatical relation identification. Through experiments using data from the Penn Treebank, we show that several of the techniques and ideas presented in this thesis are applicable not just to analysis of parent-child dialogs, but to parsing in general.
This paper presents a statistical word sense disambiguation with application in Portuguese-Chinese machine translation systems. Due to the limited availability of Portuguese-Chinese resources in the form of digital corpora and annotated Treebank, an unsupervised learning and a non-aligned bilingual corpus are applied. The proposed method first identifies words related to each of the ambiguous words based on their surrounding words and relative distance. A mathematical model is then applied in the identification of the most suitable sense of an ambiguous word in terms of the related words. All the senses discovered are converted into a set of rules and stored in the sense knowledge base for later use in disambiguation and translation process. Preliminary experiment results show an improvement of 6% in assigning correctly the corresponding translation over the baseline method.
Objective:This study aimed to examine the effects of haloperidol and amphetamine on human startle response modulated by emotionally-toned film clips. Method: Sixty participants, in two groups (one receiving haloperidol and the other receiving amphetamine) were tested using electromyography (EMG) to measure eye-blink muscle (orbicular oculi) while different emotions were induced by six 2-minute film clips. Results: An affective rating shows the negative and positive effects of the two drugs on emotional reactivity, neither amphetamine nor haloperidol had any impact on the modulation of the startle response. Conclusion: The methodological and theoretical aspects of the study and findings will be discussed.
The standard language norm fulfils two basic requirements: stability of language and its development.The former covers replacing of foreign terms with Croatian equivalents or at least their adaptation according to the rules of the Croatian language.The latter implies fulfilling new lexical needs.The economic power of the United States of America is reflected in the influence of the English language on term-formation in Croatian.Acceptance of lexical innovations is primarily gained due to thelfnguage of the media.
We describe a test-time score normalization technique (T-Norm) for text-dependent speaker verification that is robust to lexical mismatch. The main challenge to the deployment of T-Norm in a text-dependent task is the mismatch between the lexicon of the target speaker model in the application and that of the cohort speaker models. We show the negative effect of that mismatch in controlled experiments and propose a hybrid scoring scheme (T-Norm and background model) to remedy it. In a lexically mismatched scenario, which is inherent to the deployment of T-Norm in a text-dependent system, we show a 31% relative error rate reduction using the hybrid scoring over T-Norm alone. A 22% relative error rate reduction is measured over the baseline (no T-Norm) system.
Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.
This paper describes experiments carried out utilizing a variety of machine-learning methods (the k-nearest neighborhood, decision list, maximum entropy, and support vector machine), and using six machine-translation (MT) systems available on the market for translating tense, aspect, and modality. We found that all these, including the simple string-matching-based k-nearest neighborhood used in a previous study, obtained higher accuracy rates than the MT systems currently available on the market. We also found that the support vector machine obtained the best accuracy rates (98.8%) of these methods. Finally, we analyzed errors against the machine-learning methods and commercially available MT systems and obtained error patterns that should be useful for making future improvements.
The relative frequency of poor readers in Dutch general elementary education (GEE) and special elementary education (SEE) and the characteristics of their reading performance were investigated using a lexical decision procedure. According to the same norms that identified 9% of students as poor readers in GEE, no less than 73% of the students in SEE were classified as poor readers. On average, the GEE poor readers were better readers than those in SEE, but the findings do not point to substantial differences in reading processes between the two reader groups. Hypotheses about the nature of the referral process that may cause this surprisingly strong relation between poor reading ability and SEE placement are advanced.
Wordnets, which are repositories of lexical semantic knowledge containing semantically linked synsets and lexically linked words, are indispensable for work on computational linguistics and natural language processing. While building wordnets for Hindi and Marathi, two major Indo-European languages, we observed that the verb hierarchy in the Princeton Wordnet was rather shallow. We set to constructing a verb knowledge base for Hindi, which arranges the Hindi verbs in a hierarchy of is-a (hypernymy) relation. We realized that there are unique Indian language phenomena that bear upon the lexicalization vs. syntactically derived choice. One such example is the occurrence of conjunct and compound verbs (called Complex Predicates) which are found in all Indian languages. This paper presents our experience in the construction of lexical knowledge bases for Indian languages with special attention to Hindi. The question of storing versus deriving complex predicates has been dealt with linguistically and computationally. We have constructed empirical tests to decide if a combination of two words, the second of which is a verb, is a complex predicate or not. Such tests provide a principled way of deciding the status of complex predicates in Indian language wordnets.
This Research Discusses about the interference of Betawi Melayu language in Indonesia cmguage by the witters of Journal Hai. Interference is a kind of deviation in using of the norms which existing as the effect of language contact or mastery> more than one language. Beside that:t also discribes about the cause of appearing the interference the gendre of interference which - onsisting of morphology, lexical, and grammatical level.
A small subset of PDT 2.0 made available under a permissive license. Prague Dependency Treebank 2.0 (PDT 2.0) contains a large amount of Czech texts with complex and interlinked morphological (2 million words), syntactic (1.5 MW) and complex semantic annotation (0.8 MW); in addition, certain properties of sentence information structure and coreference relations are annotated at the semantic level. PDT 2.0 is based on the long-standing Praguian linguistic tradition, adapted for the current Computational Linguistics research needs. The corpus itself uses the latest annotation technology. Software tools for corpus search, annotation and language analysis are included. Extensive documentation (in English) is provided as well.
The present study examines through a genre and critical discourse analysis a total of 200 Arabic written wedding invitations in terms of their component patterns, and the role played by the broader socio-cultural norms and values in shaping this genre. It draws on two analytic frameworks from discourse: genre analysis, and critical discourse analysis (CDA). CDA has exposed at least two interrelated aspects of culture - religion and masculine authority - that have a fundamental effect on the organizational details of this communicative event, and a detailed genre analysis has identified eight generic components that are ritually drawn upon in the process of wedding invitation production. CDA results have shown how religious affiliation and masculine kinship authority not only construct and shape text component selection but also color the lexical choices and naming practices. I hope that the results of this study will be of help in further understanding the socio-cultural aspects that constrain the communicative behavior of the target language speakers, and in providing cross-cultural contrast in intercultural communication.
Computational Modeling of Bilingualism Symposium Organizer: Ping Li (pli@richmond.edu) Department of Psychology, University of Richmond Richmond, VA 23173 USA connectionist developmental lexical model (Li et al., 2004). It considers learner variables (e.g., time of L2 learning and proficiency) and input variables (word types and bilingual distance) to assess determinants of bilingual lexical acquisition. It examines the time course of acquisition, the emergence of structured lexical representations in L1 and L2, and the effect of learning history on learning plasticity. The model attempts to account for important processes such as competition, the extent to which the two lexicons compete for resources in the lexical space over time; entrenchment, the extent to which lexical structures are consolidated in L1 affects the learning of L2, and vice versa; and plasticity, the extent to which structural consolidation of L1 impacts the learning of L2. In the final talk Michael Thomas will review the recent application of connectionist models of language processing to bilingualism. Connectionist models have frequently appealed to two different architectures, localist interactive activation models and distributed processing models. These architectures have been used to explore different phenomena within bilingual language processing, including localist models of visual and auditory word recognition and distributed models of lexical and syntactic acquisition. Recent approaches employing self-organization attempt to bridge the two types of model. The range of existing models of monolingual language processing suggest clear avenues for future bilingual research to pursue, in particular focusing on dynamic aspects of (1) bilingual acquisition, (2) gradual changes in language dominance, (3) real-time switching between languages, (4) bilingual aphasia and recovery, and (5) language decay. Finally, Thomas will conclude with his recent modeling work exploring critical periods and their implications for second language acquisition. Ping Li will give an introduction and overview of the symposium at the beginning, and Yasuhiro Shirai will provide an integrative discussion at the end. Introduction Computational modeling and bilingualism have had until recently only limited interactions (see reviews in French & Jacquet, 2004; Hernandez, Li, & MacWhinney, 2005; Li & Farkas, 2002; Thomas & van Heuven, 2005). Bilingualism has been the norm rather than the exception in our globalized world, but the acquisition of two languages entails significant complexity that challenges empirical methodology. Computational modeling, because of its flexibility in parameter variation and hypothesis testing, is ideally suited for identifying mechanisms underlying bilingual language acquisition and representation. In this symposium, we propose to integrate current computational studies of bilingualism and second language acquisition. Summary of Presentations Robert French will begin by reviewing the state of the art in the study of bilingual lexical memory, pointing out crucial issues in the field. He will then present the BSRN, a bilingual simple recurrent network model. The model learns both English and French NVN strings, intermixed at the sentence level for the two languages. The simulations show that BSRN can develop distinct representations not only for individual lexical categories in each language (as in Elman, 1990), but also for the two languages in general. Thus, the model can display distinct behaviors for the bilingual’s two lexicons without invoking separate mechanisms for each language, providing evidence to the idea of “single mechanism, variable representations” from bilingualism. In the second talk Curt Burgess will present the bilingual HAL model. Using language co-occurrences to model language or memory raises a number of controversial issues on the nature of lexical and semantic representations. In addition, using lexical co-occurrence to model bilingualism introduces crucial theoretical considerations since it is incumbent on the model to account for the transformation of the different lexical codes of multiple languages into similar semantic representations. On the surface this may seem straightforward. However, since co-occurrence models function (at some point in the encoding process) by counting the number of co-occurrences between specific lexical items, one has to provide an account of how the co- occurrence vectors for L1 can merge or co-exist with the vectors for L2. Burgess will discuss this memory consolidation process, a step that is not required in high- dimensional models that encodes only one language. In the third talk Ping Li will present a self-organizing neural network model that simulates developmental stages of the bilingual lexicon. The model is based on DevLex, a References French, R., & Jacquet, M. (2004). Understanding bilingual memory: models and data. Trends in Cognitive Sciences, Hernandez, A., Li, P., & MacWhinney, B. (2005). The emergence of competing modules in bilingualism. Trends in Cognitive Sciences, 9, 220-225. Li, P., & Farkas, I. (2002). A self-organizing connectionist model of bilingual processing. In R. Heredia & J. Altarriba (eds.), Bilingual sentence processing. Elsevier. Thomas, M., & van Heuven, W. (2005). Computational models of bilingual comprehension. In J. F. Kroll & A. de Groot (eds.) Handbook of Bilingualism: Psycholinguistic Approaches. Oxford University Press.
Reduced speech fluency is frequent in clinical paediatric populations, an unexplained finding. To investigate age related effects on speech fluency variables, we analysed samples of narrative speech (picture description) of 308 healthy children, aged 5 to 17 years, and studied its relation with verbal fluency tasks. All studied measures showed significant developmental effects. Speech rate and verbal fluency scores increased, while pauses, repetitions and locution time declined with age. Speech rate correlated with semantic fluency tasks suggesting that it also depends upon the efficacy of lexical retrieval. These results indicate that the interpretation of disorders of speech fluency in childhood must incorporate age appropriate norms.
BACKGROUND: Differential responses in terms of gender and antisocial behaviour in emotional reactivity to affective pictures using the International Affective Picture System (IAPS) have been demonstrated in adult and adolescent samples. Moreover, a quadratic relationship between the arousal (intensity) and valence (degree of unpleasantness) has been suggested. The picture perception methodology has rarely been applied to middle school-aged children. We examined the subjective ratings of emotional reactivity in children for: i) the relationship between arousal and valence, ii) gender differences, and iii) its association with measures of antisocial behaviour. METHOD: Twenty-seven IAPS pictures were selected to cover a wide range of affective content and were individually administered to a non-referred community sample of 659 7-11-year-old children using a paper-and-pencil version. Concurrent symptoms of conduct disorder, oppositional defiance and psychopathy were collected from multiple sources (teacher-, parent- and self-report). RESULTS: A quadratic relationship between arousal and valence, similar to that previously reported in adults, was demonstrated. A gender difference was found for valence ratings, with girls rating aversive pictures more unpleasant than boys. No gender differences for arousal ratings were found. A significant difference was found between groups scoring above and below cut-off scores on measures of antisocial behaviour. Children above cut-off reported lower arousal to unpleasant pictures, but higher arousal to pleasant pictures. CONCLUSIONS: We confirmed that a paper-and-pencil version of the IAPS for evaluating emotion response to affectively valent and arousing stimuli can be used in school settings and that comparable gender differences in emotional reactivity can be found in children. The differential emotional reactivity of children above cut-off on measures of antisocial behaviour suggested these symptoms to be associated with a combination of increased reward and decreased punishment sensitivity.
This paper focuses on the electronic literacy practices of two Korean-American heritage language learners who manage Korean weblogs.Online users deliberately alter standard forms of written language and play with symbols, characters, and words to economize typing effort, mimic oral language, or convey qualities of their linguistic identity such as gender, age, and emotional states.However, little is known about the impact of computer-mediated nonstandard language use on heritage learners' linguistic development.Through in-depth case studies of two siblings, the study examines the linguistic and pragmatic practices of these learners online and the perceived effects of non-standard forms of computer-mediated language on their heritage language development and maintenance.The data show that electronic literacy practices provide authentic opportunities to use the language and support the development of a social network of Korean speakers, which results in greater sociopsychological attachment to the Korean language and culture.The informants report that the deviant language forms found in e-texts enable them to engage in online interactions without the pressures of having to spell the words correctly.However, they express frustrations in not being able to distinguish between correct and non-standard forms of the language, which appear to be affecting their offline language use. THE KOREAN CONTEXTThe Republic of Korea has one of the fastest-growing cybercommunities in the world.According to the Korea Network Information Center, over 63% of the entire South Korean population are Internet users, and 95% of individuals in the 6-29 age bracket report using it on a daily basis.Internet sites that enable users to create "personal spaces" to share and document their changing lives and keep connected with people they know are immensely popular among Koreans.A case in point is "Cyworld," an upgraded blog that features chatting, commentaries, pictures, music, a guest book, avatars and links to other homepages prompting users to network with their friends, family, and colleagues.As of August 2005, there are over 11 million Cyworld registered users.Participation in online forums such as Cyworld engages its members in a social process of learning through shared practices, internally constructed membership, and the formation of personal and group identities (Holmes & Jin Sook Lee Electronic literacy and heritage language maintenance Language Learning & Technology 94Myerhoff, 1999).Members are involved in a community of practice, where a group of people who come together around a joint enterprise develop common beliefs, values, and ways of doing things, which all influence the ways in which members communicate with one another (Eckert, 2000;Wenger, 1998).New forms of expression are constantly being negotiated and shared among online users, making it difficult to keep current with the changing face of electronic text.Computer-mediated communication is unique in that, despite its similarities to oral speech, it invites substantial deregulation effects on communication, which can foster the use of creative, non-standard language play (Sproull & Kiesler, 1986).Studies have documented non-standard 1 uses of language in online interactions (a) to mark certain individual characteristics such as provincial dialects, social class, gender, age, and/or personality traits, (b) to economize typing efforts, and/or (c) to mimic spoken language (Barnes, 2003;Herring, 2001;Song, 2002;Sproull & Kiesler, 1986).For example, Su ( 2004) found an emergent mock Taiwanese accent among Internet users as a form of language play to jointly construct "a young, lively, congenial, and witty presence" (p.61).Androutsopoulos ( 2000) also revealed that non-standard orthography in online fan media texts was representative of spoken language and purely graphemic modifications, which are used to serve as contextualization cues and cues of subcultural positioning.Although all natural languages inevitably change over time, drastic deviances from standard language ranging from non-standard orthography and incorrect grammar to unfamiliar lexical items and symbols have brought forth great concern about the preservation of standard orthography, grammar, and pragmatic uses of the Korean language (Choi, 2003;Kim, 2005;Park, 1989).Educators across grade levels in Korea are reporting that students display electronic textual features in their school work: they have difficulty with spelling and with the proper word spacing used to delineate word boundaries due to non-standard ways of Internet language use, which flout conventional norms of literacy practices (Ahn, 2000;Choi, 2003;Kim, 2005;Noh, 2000).For young children and Korean as foreign/second language learners who have not fully acquired literacy in the language, exposure to electronic texts may have adverse effects on their language development.However, Meskill, Mossop, and Bates (1999) state that "children in the age of electronic text are developing unique skills and strategies for inventing novel forms of understanding these texts that are quite often independent of formal instructional ('school') literacy training" (p.4), thus, highlighting the positive ways in which the development of electronic texts can benefit students' cognitive flexibility and skills.
General recognition theory (GRT) is both a theory of categorization and a framework for studying human categorization behavior. The GRT toolbox is a set of MATLAB scripts and subroutines that can help an experimenter design categorization experiments, generate stimuli for these experiments, simulate a participant’s responses, analyze categorization data, and graph results. The typical user designs experiments for two-category tasks in which the categories are specified by multivariate normal distributions. The toolbox also provides tools for fitting the general linear classifier and the general quadratic classifier to a data set.
Abstract The paper is an attempt, guided by the principles of Descriptive Translation Studies, to ‘detect’ and ‘describe’ the various types of shifts, in the area of lexical repetition, which have occurred in an Arabic–English translation. The study also tries to ‘explain’ the underlying factors which may have prompted the various decision-making processes behind these translation shifts. It is postulated that any translation product represents an intertext which carries the ‘finger-prints’ of the norms of its SL and culture. Moreover, translation as a retextualizing process is bound to be directed by the norms of the TL and its culture. The two poles of SL ‘adequacy’ norms and TL ‘acceptability’ norms have thus been at the background during the description, taxonomy, and explanation of the various types of shifts in lexical repetition detected in the study corpus. Different instances of shifts have been found to fall under three main categories: (a) Shifts which avoid or minimize lexical repetition; (b) Shifts which announce repetition by retaining it, though with some modifications; and (c) Shifts which emphasize lexical repetition by expanding it. Most shifts, it has been found, belong to the first category. A lengthy discussion of the possible causes which could have motivated the translator to perform these various shifts has come to the conclusion that the textual and cultural norms of the TL seem to play the major role in the operation. In order to ascertain that the above conclusion is not attributable to the ‘hegemony’ of the TL (English), nor to the individual translator or to the type of text being analyzed, a number of follow-up studies is proposed at the end. Résumé Guidé par les principes des études de traduction descriptive, l’article est une tentative de « détecter » et de « décrire » les différents types de changements dans le domaine de la répétition lexicale, qui se sont présentées dans une traduction arabe-anglais. L’étude cherche également à « expliquer » les facteurs sous-jacents qui peuvent avoir provoqué les différents processus de prise de décision derrière ces changements de la traduction. On pose comme principe que tout produit d’une traduction représente un intertexte, qui porte les «empreintes digitales » des normes de sa langue-source et de sa culture. De plus, la traduction, en tant que processus de retextualisation, est nécessairement guidé par les normes de la langue-cible et de sa culture. Par conséquent, les deux pôles des normes « de justesse » de la langue-source et des normes «d’admissibilité » de la langue-cible se trouvaient à l’arrière-plan, pendant la description, la taxonomie et l’explication des différents types de changements de la répétition lexicale, détectées dans le corpus de l’étude. On a remarqué que les différents exemples de changements s’inscrivaient dans trois catégories principales: (a) les changements qui évitent ou minimisent la répétition lexicale; (b) les changements qui annoncent une répétition en la conservant; et (c) les changements qui soulignent la répétition lexicale en la développant. On a découvert que la plupart des changements appartiennent à la première catégorie. Une longue discussion sur les causes possibles, qui peuvent avoir poussé le traducteur à effectuer ces divers changements, a abouti à la conclusion que les normes textuelles et culturelles de la langue-cible semblent jouer un rôle majeur dans l’opération. Un certain nombre d’études complémentaires sont proposées, afin de vérifier que la conclusion ci-dessus n’est imputable ni à « l’hégémonie » de la langue-cible (anglais), ni au traducteur individuel, ni au type de texte analysé.
This paper describes a peer-to-peer architecture for representing and disseminating linguistic corpora, linguistic annotation, and resources such as lexical databases and gazetteers. The architecture is based upon a ‘Universal Database’ technology in which all information is represented in globally identified, extensible bundles of attribute-value pairs. These objects are replicated at will between peers in the network, and the business rules that implement replication involve checking digital signatures and proper attribution of data, to avoid information being tampered with or abuse of copyright. Universal identifiers enable comprehensive standoff annotation and commentary. A carefully constructed publication mechanism is described that enables different users to subscribe to material provided by trusted publishers on recognized topics or themes. Access to content and related annotation is provided by distributed indexes, represented using the same underlying data objects as the rest of the database.
cjelokupni tekst: Abstract: From the translator's point of view, collocations and idioms belong to rather demanding text units, which often require a high level of linguistic, communicative, cultural and translational competence. The translator needs to be aware, and appreciative of their semantics (the difficulty with idioms being that their meaning is not deducible from that of the individual elements), their syntax (non-free and sometimes puzzling), their pragmatics (related to a variety of linguistic and textual circumstances, more specific of which can stem from conscious breach of the frozen syntax, the metaphorical quality of their meaning or culture-specific usage patterns) on both the source and the target end of the translation process. In addition, a successful choice of an appropriate equivalent requires a well-founded translational decision as to the most relevant aspect(s) of the value of the phrase in question i.e. the aspect which should be matched in the translation, as well as an awareness of the various procedures that can be employed. The paper discusses translation equivalents of Swedish collocations and idioms manifest in Croatian translations of about 1000 book pages of Swedish fiction. In an attempt to check whether there are any patterns in the treatment of collocations and idioms in translation, the discussion focuses on the following characteristics of the established equivalents: - whether they are the same type of linguistic units as the original phrase (collocation or idiom); - which aspect of the original phrase’ s linguistic and communicative value has been given prominence in the translation (i.e. is best matched by the chosen translation equivalent); - whether they can be considered lexical or grammatical calques (if yes, of what kind). The basis for the discussion is provided by twofold procedure: - a systematic analysis of all the translation equivalents of ten Swedish lexical collocations / idioms established in the translation of seven books of fiction; - an analysis of the equivalents of some other lexical collocations and idioms established in randomly selected extracts from three other novels. The analysis is primarily expected to offer an insight into the ways in which lexical collocations and idioms are commonly perceived and treated. In addition it will feed into a more general picture of translation practices and translation norms in Croatia.
This paper aims at developing methods of extracting figurative expressions from a domain-specific corpus and extending the multi-lingual lexical database entries for those expressions to be included. The nominal entries which can be used figuratively are selected from the annotated corpus, using the hierarchical semantic class of Sejong Electronic Dictionary. And from the raw corpus, the partially-parsed corpus are constructed automatically. To extract candidates for figurative expression, we fixed some syntactic patterns in advance, for example [NP+sbj-marker NP+obj-marker V], and extract those patterns from partially-parsed corpus. After investigating the extracted expressions and classifying them whether figurative or literal, we concluded that some nominal entries are used more figuratively in specific syntactic patterns.
DEB II platform is a new language independent development platform for lexicographic tools based on the client/server architecture. It uses web Mozilla Development Platform for building special interface modules allowing to build the resulting lexicographic application such as a dictionary writing system from several components. The DEB II consists of a dictionary browser and editor for more XML dictionaries, an integrated Czech morphological analyzer and can cooperate with other applications such as corpus manager Manatee/Bonito and Word Sketch Engine or a geographical information system GRASS (used for building a Czech onomastic dictionary). The properties and assets of the DEB II platform will be presented as one of its current applications, the tool named PRALED, which is designed for preparation of the new Czech Lexical Database in the Institute of Czech Language in Prague.
Previously, we introduced a new computational tool for nonlinear curve fitting and data set exploration: the Naturalistic University of Alberta Nonlinear Correlation Explorer (NUANCE) (Hollis & Westbury, 2006). We demonstrated that NUANCE was capable of providing useful descriptions of data for two toy problems. Since then, we have extended the functionality of NUANCE in a new release (NUANCE 3.0) and fruitfully applied the tool to real psychological problems. Here, we discuss the results of two studies carried out with the aid of NUANCE 3.0. We demonstrate that NUANCE can be a useful tool to aid research in psychology in at least two ways: It can be harnessed to simplify complex models of human behavior, and it is capable of highlighting useful knowledge that might be overlooked by more traditional analytical and factorial approaches. NUANCE 3.0 can be downloaded from the Psychonomic Society Archive of Norms, Stimuli, and Data at www.psychonomic.org/archive.
Web searchers reformulate their queries, as they adapt to search engine behavior, learn more about a topic, or simply correct typing errors. Automatic query rewriting can help user web search, by augmenting a user’s query, or replacing the query with one likely to retrieve better results. One example of query-rewriting is spell-correction. We may also be interested in changing words to synonyms or other related terms. For Japanese, the opportunities for improving results are greater than for languages with a single character set, since documents may be written in multiple character sets, and a user may express the same meaning using different character sets. We give a description of the characteristics of Japanese search query logs and manual query reformulations carried out by Japanese web searchers. We use characteristics of Japanese query reformulations to extend previous work on automatic query rewriting in English, taking into account the Japanese writing system. We introduce several new features for building models resulting from this difference and discuss their impact on automatic query rewriting. We also examine enhancements in the form of rules which block conversion between some character sets, to address Japanese homophones. The precision/recall curves show significant improvement with the new feature set and blocking rules, and are often better than the English counterpart.
This special issue on Data Resources, Evaluation, and Dialogue Interaction is based on five thoroughly revised and extended papers from the sixth SIGdial Workshop held in Lisbon, Portugal, in September 2005. SIGdial is a special interest group on discourse and dialogue whose parent organisations are the Association for Computational Linguistics (ACL) and the International Speech Communication Association (ISCA). SIGdial workshops accommodate a broad range of topics related to discourse and dialogue. Among these topics are data resources, evaluation, and dialogue interaction. The papers selected for this special issue have in common that they all deal with aspects of these topics and each paper has its focus on at least one of them.
This paper describes a methodology aimed at grouping Catalan verbs according to their syntactic behavior. Our goal is to acquire a small number of basic classes with a high level of accuracy, using minimal resources. Information on syntactic class, expensive and slow to compile by hand, is useful for any NLP task requiring specific lexical information. We show that it is possible to acquire this kind of information using only a POS-tagged corpus. We perform two clustering experiments. The first one aims at classifying verbs into transitive, intransitive and verbs alternating with a se-construction. Our system achieves an average 0.84 F-score, for a task with a 0.33 baseline. The second experiment aims at further distinguishing among pure intransitives and verbs bearing a prepositional object. The baseline for the task is 0.51 and the upperbound 0.98. The system achieves an average 0.88 F-score.
Studies on attribution in the moral domain often involve the use of specific behavior examples. To make valid comparisons across trait dimensions (such as honesty and friendliness), it is important to equate the intensities of the specific behaviors used. Pretesting specific behaviors can be a costly effort, but it is often necessary for research in social psychology. Our study provides a rich source of such pretested behaviors. Positive and negative examples of behaviors in the categories of honesty, loyalty, friendliness, charitableness, and cooperativeness were solicited from participants and then rated on the relevant trait dimension by an independent group. The result is data representing rankings, raw scores, andz-scores in an index of 500 behaviors across 10 trait categories that can be used by researchers to study moral and immoral behaviors. The full index of behaviors is available at www .psychonomic.org/archive/.
In this paper, we address the issue of generating in-domain language model training data when little or no real user data are available. The two-stage approach taken begins with a data induction phase whereby linguistic constructs from out-of-domain sentences are harvested and integrated with artificially constructed in-domain phrases. After some syntactic and semantic filtering, a large corpus of synthetically assembled user utterances is induced. In the second stage, two sampling methods are explored to filter the synthetic corpus to achieve a desired probability distribution of the semantic content, both on the sentence level and on the class level. The first method utilizes user simulation technology, which obtains the probability model via an interplay between a probabilistic user model and the dialogue system. The second method synthesizes novel dialogue interactions from the raw data by modelling after a small set of dialogues produced by the developers during the course of system refinement. Evaluation is conducted on recognition performance in a restaurant information domain. We show that a partial match to usage-appropriate semantic content distribution can be achieved via user simulations. Furthermore, word error rate can be reduced when limited amounts of in-domain training data are augmented with synthetic data derived by our methods.
This paper describes one of the ways how to overcome some of the major limitations of current fulltext search engines. It deals with synonymy of the web search engine results by clustering them into rele- vant synonym category of given word. It employs WordNet lexical database and several linguistic approaches to classify results in search engine re- sult page (SERP) in appropriate synonym category according to Word- Net synsets. Some methods to refine the classification are proposed and some initial experiments and results are described and discussed.
The Czech Academic Corpus version 1.01 is a corpus with a manual annotation of morphology of the Czech language consisting of approximately 600,000 words in continuous texts. The process and the size of the Czech Academic Corpus (CAC) project differs from every traditional project. The primary goal of this project was to create a computerized corpus that would contain manual annotation of morphology and syntax of Czech. This manual annotation of morphology and syntax was initially developed more than twenty years ago (1971-1985) at the Institute of the Czech Language of the Czech Academy of Science as a basis for constructing a frequency dictionary of Czech at that time. Having mentioned the years when the history of CAC has started we cannot miss the fact that there were available two computerized annotated corpora in the 1960s Brown Corpus of American English and LOB Corpus of British English. Both corpora became well known to the corpus linguists whereas CAC (although containing richer annotation schemes) has remained hidden mainly because of the political regime of the 1980s in the Czech Republic. Fortunately for Czech computational linguistics, CAC was (and still is, obviously) of significant importance because the very first experiments on the corpus-based processing of Czech could be performed thanks to CAC. Independent from CAC, the project of the Prague Dependency Treebank (PDT) was launched in 1996. The complexity of the PDT three-layer annotations (morphological, syntactic-analytical, tectogrammatical) is reflected in the volume of the annotated data 2 million words are annotated only morphologically, 1,5 million words have also an analytic annotation and from them 800,000 words is provided with tectogrammatical annotation. The second version of PDT has been released in summer 2006 (Hajic et al., 2006), (PDT 2.0, 2006). The experience acquired from annotating such a huge volume of data is so exceptional and illuminating that it has become one of the main motivations for further work within CAC the idea of converting the internal format and annotation schemes of CAC in a way that they would be compatible within PDT was proposed. This conversion will facilitate the possibility of integrating CAC annotations directly into PDT. The currently released first version of CAC (CAC 1.0, 2006) is a result of conversion of the internal format and morphological annotations. The guide to the CAC 1.0 (Hladka et al., 2006) is a road map to the CD-ROM which offers:
In this thesis lateralization of olfactory functions was investigated by both behavioral and electrophysiological assessment, the latter with the olfactory event-related potential (OERP) technique. The olfactory sense is primarily ipsilateral in that a stimulus that is presented to one nostril is initially processed in the same hemisphere. This makes it possible to observe differences between stimulated nostrils as an indication of hemispheric difference. Study I explored differences in olfactory cognitive functions with respect to side of rhinal stimulation and demonstrated that familiarity ratings are higher at right- compared to left-nostril stimulation. No differences were found in episodic recognition memory or free identification, possibly reflecting inter-hemispheric interactions in higher cognitive functions. Effects of repetition priming were present in odor identification and tended to be more pronounced when tested via left nostril. Study II further investigated the effect of previous exposure in odor identification by a different experimental set-up, and demonstrated effects of repetition priming when tested via left- but not right-nostril stimulation. This finding indicates the importance of reconsidering possible sequential effects in olfactory research. Study III examined methodological aspects of an OERP protocol with respect to stimulus duration, which was used in Study IV. No differences in amplitudes or latencies where found between the stimulus durations of 150, 200 and 250 ms, suggesting the commonly used duration of 200 ms in a standard protocol. Study IV investigated laterality effects in OERPs with respect to side of stimulation and electrode site. The results showed consistent amplitudes and latencies regardless of rhinal side of stimulation. Larger amplitudes were demonstrated on left hemisphere and midline compared to right hemisphere, possibly explained by smaller N1/P2 amplitudes at the right-hemisphere sites at left-nostril stimulation. Apart from a proposed OERP protocol, the findings support the notions of a right-hemisphere predominance in processes related to olfactory perception and indicate, in accordance with other findings, a left-side advantage in conceptual repetition priming.
Celebrity Recognition Priming: Is Association Required? Lara L. Jones (laraj@uga.edu) Adam Pope (adrepo@uga.edu) Eva Bonney Reed (bonreed@uga.edu) Patrick Thompson (thompson.patrick.d@gmail.com) Elizabeth Cooper (lizzie23@uga.edu) Kevin Wilson (iamag2@uga.edu) Department of Psychology, University of Georgia Psychology Building, Athens, GA 30602 USA from a musical artist familiarity task (n = 50) on the basis of having no association with the target and having a familiarity rating ≥ 5.00. Finally, 34 participants rated the similarity between the target and each of the three Prime- types (counterbalanced across three lists). The categorical primes (M = 4.88, SE =.14) were reliably more similar than the associative primes (M = 3.99, SE =.21) and the unrelated primes (M = 2.38, SE =.09), both ps <.05. Participants judged whether each of 72 target names was a known celebrity name. The experimental trials consisted of 18 related (either associative or categorical) prime-target trials, 18 unrelated prime-target trials (e.g., Sting AE Adam Sandler), and 36 filler trials consisting of fictional target names (e.g., Bruce Willis AE Carl Spencer). Each prime celebrity name was displayed on a computer screen for 500 msec, followed by a 1500 msec blank screen, and then the target name until a response was provided. Does the semantic organization of actors consist of only associative links (e.g., former co-stars in a popular movie)? Or can two actors share a purely categorical link? Previous studies on celebrity recognition have found that celebrity names (e.g., Adam Sandler) were recognized faster following presentation of an associated person (e.g., Drew Barrymore). Yet the evidence for semantic priming without association (i.e., “categorical priming”; Jimmy Fallon AE Adam Sandler) is equivocal (see Carson & Burton, 2001). Several possible reasons could account for the lack of reliable categorical priming including: target familiarity, prime and target similarity (see McRae & Boisvert, 1998), and stimulus onset asynchrony (SOA), with longer SOAs required for categorical than associative priming. We more closely controlled these critical factors to re-examine whether celebrity names would be recognized faster following an associatively or categorically related celebrity. Prime-type (associative vs. categorical) was a between- participants factor to prevent the robust associative relation from overshadowing the weaker categorical relation. Results and Discussion Overall, targets were recognized faster following the related primes (M = 757, SE = 13) than the unrelated primes (M = 784, SE = 13), p <.01. The Prime-type × Relation interaction was not reliable (p =.64). Critically, the related items were judged faster than the unrelated items within both the associative condition (31 msec; p <.05) and the categorical condition (23 msec; p <.05). Thus, results indicate that people belonging to the same category may be organized on the basis of similarity in addition to association. Method Participants University of Georgia undergraduates participated in the experiment for course credit and were randomly assigned to the associative (n = 53) or to the categorical (n = 51) Prime- type condition. An additional 196 undergraduates participated in the stimulus-norming tasks described below. Table 1: Response Times (msec); Standard errors are in parentheses Materials and Procedure Participants (n = 52) rated the familiarity of 268 actor names on a scale from 1 (unfamiliar) to 7 (very familiar). From these names, 140 were selected on the basis of having familiarity ratings ≥ 5.00 for inclusion in the association task, wherein participants (n = 60) provided the name of the first person who came to mind for the presented celebrity. Both forward and backward association probabilities were calculated for a selected 36 associatively-related prime- target pairs (M =.35, SE =.04 and M =.23, SE =.03). Celebrities that were similar to these targets were generated by the authors to serve as categorical primes. These primes were from the same actor category but were unassociated with the target. Thirty-six unrelated primes were selected Prime-type Associative Categorical Related Unrelated References Carson, D. R. & Burton, A. M. (2001). Semantic priming of person recognition: Categorical priming may be a weaker form of the associative priming effect. The Quarterly Journal of Experimental Psychology, 54A, 1155-1179. McRae, K. & Boisvert, S. (1998). Automatic semantic similarity priming. Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 558-572.
There are many methods to improve performances of statistical parsers. Among them, resolving structural ambiguities is a major task. In our approach, the parser produces a set of n-best trees based on a feature-extended PCFG grammar and then selects the best tree structure based on association strengths of dependency word-pairs. However, there is no sufficiently large Treebank producing reliable statistical distributions of all word-pairs. This paper aims to provide a self-learning method to resolve the problems. The word association strengths were automatically extracted and learned by parsing a giga-word corpus. Although the automatically learned word associations were not perfect, the built structure evaluation model improved the bracketed f-score from 83.09 % to 86.59%. We believe that the above iterative learning processes can improve parsing performances automatically by learning word-dependence knowledge continuously from web. 1.
In this paper, we present a novel approach for contextual and concept based query formulation in web-based information retrieval, which is an on-going PhD project being undertaken at the Software Engineering Research Lab (SERL) at Auckland University of Technology (AUT). Various query formulation approaches have been studied for a long time with varying degree of success. To the best of our knowledge none of the existing approaches offer a similar service to the one discussed in this paper. \nOur novel approach centres on the formulation of a high quality search query using a user’s contextual profile, a shared contextual knowledge based, lexical databases and domain-specific concepts. A user’s contextual profile is constructed by monitoring and capturing user’s implicit and explicit data. A shared contextual knowledge based is built by consolidating various users’ contextual profiles. A machine learning technique is employed to learn user’s specific information needs and support the iterative development of a search query by suggesting alternative terms/ concepts for query formulation. Early results indicate that the system has the potential to not only aid in the formulation of high quality search queries but also contribute towards the long term goal of intelligent contextual information retrieval from the WWW.
Valency of lexical units (i.e. the sets of their obligatory and optional dependents) constitutes the main link between lexicon and grammar. As handled up to now by J. Panevova and others in the Functional Generative Description, valency provides a very good starting point for the testing of this approach in the Prague Dependency Treebank. The morphemic and especially syntactic annotation of large segments of free texts confirm that this description has essentially been formulated adequately. Even so, certain issues of valency deserve further discussion. This article partly summarizes earlier research in the Charles University Theoretical and Computational Linguistics group and adds new results. It aims to document how issues concerning a hierarchy of the types of dependency relations, the orientation of these relations, the usefulness of recognizing a third class of dependents “between” arguments and adjuncts, etc., can be handled in useful ways using this background.