Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
16504 papers
Visual psychophysicists, who study object, color, and light perception, have a demand for software that produces complex but, at the same time, physically accurate stimuli for their experiments. The number of computer graphic packages that simulate the physical interaction of light and surfaces is limited, and mostly they require the purchase of a license. RADIANCE (Ward, 1994), however, is freely available and popular in the visual perception community, making it a prime candidate. We have shown previously that RADIANCE’S simulation accuracy is greatly improved when color is coded by spectra, rather than by the originally envisaged RGB triplets (Ruppertsberg & Bloj, 2006). Here, we present a method for spectral rendering with RADIANCE to generate hyperspectral images that can be converted to XYZ images (CIE 1931 system) and then to machine-dependent RGB images. Generating XYZ stimuli has the added advantage of making stimulus images independent of display devices and, thereby, facilitating the process of reproducing results across different labs. Materials associated with this article may be downloaded from www.psychonomic.org.
Reviews the book, Le Francais en Amérique du Nord: État présent by Albert Valdman, Julie Auger, and Deborah Piston-Hatlen (eds.) (2005). Poirier, Boivin, Trepanier & Verreault 1994 gave us the first general overview of the French linguistic legacy in North America. Valdman and his team have updated that work, incorporating the findings of sociolinguistic research carried out over the past decade, notably in language obsolescence. The result is comprehensive treatment of all the main areas of North America where French is spoken. It is well organized, with an introductory chapter providing a succinct overview of the four sections to follow: The first describes where, how, and to what extent French is spoken in North America; the second examines language variation in each of these areas and the effects of language contact; the third looks at linguistic norms and language planning; and a fourth is devoted to more general comparative and historical issues. It is possible to point to improvements that could have been incorporated into the volume. There are occasional production blemishes. However, this volume offers an invaluable tool not only for students of French but also for sociolinguists concerned with the effects of language contact, language change, and language obsolescence. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
Background: Genome-wide data provide a powerful tool for inferring patterns of genetic variation and structure of human populations. Principal Findings: In this study, we analysed almost 250,000 SNPs from a total of 945 samples from Eastern and Western Finland, Sweden, Northern Germany and Great Britain complemented with HapMap data. Small but statistically significant differences were observed between the European populations (FST = 0.0040, p<10-4), also between Eastern and Western Finland (FST = 0.0032, p<10-3). The latter indicated the existence of a relatively strong autosomal substructure within the country, similar to that observed earlier with smaller numbers of markers. The Germans and British were less differentiated than the Swedes, Western Finns and especially the Eastern Finns who also showed other signs of genetic drift. This is likely caused by the later founding of the northern populations, together with subsequent founder and bottleneck effects, and a smaller populatio)
The semantic annotation of texts with senses from a computational lexicon is a complex and often subjective task. As a matter of fact, the fine granularity of the WordNet sense inventory [Fellbaum, Christiane (ed.). 1998. WordNet: An Electronic Lexical Database MIT Press], a de facto standard within the research community, is one of the main causes of a low inter-tagger agreement ranging between 70% and 80% and the disappointing performance of automated fine-grained disambiguation systems (around 65% state of the art in the Senseval-3 English all-words task). In order to improve the performance of both manual and automated sense taggers, either we change the sense inventory (e.g. adopting a new dictionary or clustering WordNet senses) or we aim at resolving the disagreements between annotators by dealing with the fineness of sense distinctions. The former approach is not viable in the short term, as wide-coverage resources are not publicly available and no large-scale reliable clustering of WordNet senses has been released to date. The latter approach requires the ability to distinguish between subtle or misleading sense distinctions. In this paper, we propose the use of structural semantic interconnections—a specific kind of lexical chains—for the adjudication of disagreed sense assignments to words in context. The approach relies on the exploitation of the lexicon structure as a support to smooth possible divergencies between sense annotators and foster coherent choices. We perform a twofold experimental evaluation of the approach applied to manual annotations from the SemCor corpus, and automatic annotations from the Senseval-3 English all-words competition. Both sets of experiments and results are entirely novel: structural adjudication allows to improve the state-of-the-art performance in all-words disambiguation by 3.3 points (achieving a 68.5% Fl-score) and attains figures around 80% precision and 60% recall in the adjudication of disagreements from human annotators. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
There is an increasing interest in multimodal communication as suggested by several national and international projects (ISLE, HUMAINE, SIMILAR, CHIL, AMI, CALO, VACE, CALLAS), the attention devoted to the topic by well-known institutions and organizations (the National Institute of Standards and Technology, the Linguistic Data Consortium), and the success of conferences related to multimodal communication (ICMI, IVA, Gesture, Measuring Behavior, Nordic Symposium on Multimodal Communication, LREC Workshops on Multimodal Corpora).
In my thesis I have attempted to develop an integrated translation approach materialized in the form of a Dynamic Translation Model (DTM). This endeavour can be justified to the extent that Translation Studies is perceived so far as a fragmentary discipline with implicitly and explicitly opposed and apparently irreconcilable points of view: linguistics-oriented approaches and culture-and-literature-oriented approaches. The main problem arising from this lack of common ground for further developing Translation Studies is that the disciplinary boundaries are not well-established and therefore the discipline itself cannot be developed coherently. Besides, Translation Studies is still to be constructed as an autonomous and an independent discipline that has a common core of theoretical and practical problems. This lack of coherent development of the discipline is due, I think, to an epistemological mistake: to believe that one single approach can account for (that is, describe and explain) all the translational reality. I propose to distinguish a two-phase epistemological move: 1. each translation approach works on its own research interests and acknowledges that its approach deals only with one part of the whole subject matter of Translation Studies; and 2. the results obtained by each translation approach are incorporated into a holistic integrative model like the Dynamic Translation Model I propose. In order to achieve this goal I have attempted to show the key tenets of modern translation approaches, both linguistics-oriented and culture-and-literature-oriented, by quoting the main theses of the representatives of these approaches. I have then presented the most important criticisms that have been raised in relation to these diverse translation approaches, together with my own criticisms (chapters 1 and 2). Also, I have introduced the theoretical basis for an integrated approach taking Holmes’ differentiation between theoretical (product-, process-, and function-oriented) and practical approaches as a point of departure. Likewise, I have discussed the problems of integrating Translation Studies, as well as Snell-Hornby’s integrated proposal and some key aspects of literary translation relevant for my integrative endeavour (chapter 3). Finally, I have developed my proposal for a Dynamic Translation Model (chapter 4). As to the conclusions of my thesis, I can say that my holistic DTM was able to integrate functionally aspects from both linguistics-oriented and culture-and-literature-oriented approaches: historico-cultural context (Leipzig School and postcolonial studies); norms, ideology and power (Descriptive Translation Studies; G. Toury and A. Lefevere); translation commisioner (Skopos theory); sender’s communicative purpose (linguistic and pragmatic approaches: W. Koller, J. House, H. Gerzymisch-Arbogast, etc); importance of source language text (linguistic and textlinguistic approaches; stylistic approaches; B. Spillner, B. Sandig); translator’s comprehension process (hermeneutic, deconstructive, and poststructural approaches), target language receiver in the target language historico-cultural context (Descriptive Translation Studies; postcolonial and gender studies). On the other hand, the three levels of the Dynamic Translation Model help to explain the flux of translational proceses and the variables that are activated or neutralized therein. They also incorporate concepts from other disciplines such as text linguistics, pragmatics, stylistics, and the communication theory. In my integrative endeavour I also proposed new concepts and, accordingly, coined new terms: Compulsory Translational Forces (CTF) (which include both Initiator’s Translational Instructions (ITI) and Target Language Valid Translational Norms (TL-VTN), Default Equivalence Position (DEP). In the pragmatic dimension of the model special attention is paid to what I call Text Illocutionary Indicators (TII) as well as the strengthening (upgraders) and weakening (downgraders) illocutionary mechanisms in relation to the Source Language Text (SLT) and the Target Language Text (TLT). Semantic/lexical fields play a crucial role in the establishment of equivalences between SLT and TLT in the text semantic dimension, as well as what I have called Fictionalizing Stylistic Shifts in the text stylistic dimension. As to the future developments of translation research within the framework of the Dynamic Translation Model I would say that some modificationbs may be called for so that interpretation can also be accounted for. This proposal can be used profitably in the field of translation criticism. As is the case with any other integrative approach, DTM should be widely discussed and criticized in order to validate its theoretical soundness and its application in Translation Studies. This thesis is an attempt to contribute in this research direction.
This study investigated cued odor identification performance with a set of 64 natural common odors (half of edible and half of nonedible stimuli) in three groups of participants: one group of 30 young adults (mean age 25.3 years, range 18–30, SD 3.1) and two groups of older adults—20 young-old (mean age 64.4 years, range 60–69, SD 2.8) and 21 old-old (mean age 74.6 years, range 70–79, SD 2.5). The results showed that 49 of the 64 odors were correctly identified by over 70% of the participants in all groups. The odor identification performance of the young-old adults did not differ from that of the young adults. However, the oldest group showed a significant loss of performance in the task. Women in the young-old group performed better than men, whereas no gender differences were found in the other two age groups. The data obtained in this study will be useful for further perceptual and memory studies conducted in the olfactory modality with young as well as with older participants.
ABSTRACT Using lexical items from Martin Durrell's classification of register variation as a sample, the study investigates how the current advanced monolingual learners' dictionaries of German as an additional language treat such variation and indicate to their users what they consider to be standard usage: how do they set the standard? Abbreviated usage labels as conventionally found in dictionaries for first‐language users are the primary indications, and the dictionaries seldom go beyond such labels. German Standard German is the norm. At its core are unmarked or unlabelled items, while its range extends to include less formal items from everyday use, especially spoken, which are typically labelled umg. or gespr., and more formal items, more particularly found in written usage, which are labelled geh. or geschr. Non‐standard items, if entered as headwords, may be labelled derb or vulgär, veraltet or lit. No one dictionary stands out from the others as setting the standard in terms of treating register variation, and it must be questioned whether learners of German as an additional language would not be better served by more detailed, discursive information on different contexts of use and stylistic levels.
Recent neuroimaging studies have identified a set of brain regions that are metabolically active during wakeful rest and consistently deactivate in a variety the performance of demanding tasks. This ''default network'' has been functionally linked to the stream of thoughts occurring automatically in the absence of goal-directed activity and which constitutes an aspect of mental behavior specifically addressed by many meditative practices. Zen meditation, in particular, is traditionally associated with a mental state of full awareness but reduced conceptual content, to be attained via a disciplined regulation of attention and bodily posture. Using fMRI and a simplified meditative condition interspersed with a lexical decision task, we investigated the neural correlates of conceptual processing during meditation in regular Zen practitioners and matched control subjects. While behavioral performance did not differ between groups, Zen practitioners displayed a reduced duration of the neur)
Real-time communication platforms such as ICQ, MSN and online chat rooms are getting more popular than ever on the Internet. There are, however, real risks where criminals and terrorists can perpetrate illegal and criminal abuses. This highlights the security significance of accurate detection and translation of the chat language to its stand language counterpart. The language used on these platforms differs significantly from the standard language. This language, referred to as chat language, is comparatively informal, anomalous and dynamic. Such features render conventional language resources such as dictionaries, and processing tools such as parsers ineffective. In this paper, we present the NIL corpus, a chat language text collection annotated to facilitate training and testing of chat language processing algorithms. We analyse the NIL corpus to study the linguistic characteristics and contextual behaviour of a chat language. First we observe that majority of the chat terms, i.e. informal words in a chat text, is formed by phonetic mapping. We then propose the eXtended Source Channel Model (XSCM) for the normalization of the chat language, which is a process to convert messages expressed in a chat language to its standard language counterpart. Experimental results indicate that the performance of XSCM in terms of chat term recognition and normalization accuracy is superior to its Source Channel Model (SCM) counterparts, and is also more consistent over time.
We survey the evaluation methodology adopted in information extraction (IE), as defined in a few different efforts applying machine learning (ML) to IE. We identify a number of critical issues that hamper comparison of the results obtained by different researchers. Some of these issues are common to other NLP-related tasks: e.g., the difficulty of exactly identifying the effects on performance of the data (sample selection and sample size), of the domain theory (features selected), and of algorithm parameter settings. Some issues are specific to IE: how leniently to assess inexact identification of filler boundaries, the possibility of multiple fillers for a slot, and how the counting is performed. We argue that, when specifying an IE task, these issues should be explicitly addressed, and a number of methodological characteristics should be clearly defined. To empirically verify the practical impact of the issues mentioned above, we perform a survey of the results of different algorithms when applied to a few standard datasets. The survey shows a serious lack of consensus on these issues, which makes it difficult to draw firm conclusions on a comparative evaluation of the algorithms. Our aim is to elaborate a clear and detailed experimental methodology and propose it to the IE community. Widespread agreement on this proposal should lead to future IE comparative evaluations that are fair and reliable. To demonstrate the way the methodology is to be applied we have organized and run a comparative evaluation of ML-based IE systems (the Pascal Challenge on ML-based IE) where the principles described in this article are put into practice. In this article we describe the proposed methodology and its motivations. The Pascal evaluation is then described and its results presented.
Reply by the current authors to the review by Constant Leung (see record [rid]2008-09991-006[/rid]) on the original book, Language testing: The social dimension (2006). Leung has drawn attention to possibly the most obvious gap in our treatment: a properly elaborated discussion of the assessment of English as a lingua franca. While consideration of this issue has begun in the work of authors he cites in his review, and elsewhere, it is, as Leung points out, a multiply complex issue, in which the social dimension is the crux of the problem, ‘in terms of speaker subject positions, lexicogrammatical norms, transcultural pragmatic conventions and so on’. It is clear that language testing—particularly significant here as a site of authority about linguistic norms, not unlike a dictionary—has an important role to play in authorizing or de-authorizing English as a lingua franca communication as a proper target for language learning; a further demonstration, if one were needed, of the power of tests. But beyond this political and institutional dimension, the psychometric problems inherent in designing tests based on a construct that is local, situated, and fluid pose a difficult but productive challenge to testers. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
Correct identification of word meaning is a long-standing problem for lexicography, language teaching, linguistic theory, and computer processing of text. Traditional approaches typically proceed word by word, relying on evidence from introspection – and have failed. A new theory of meaning is needed. In this prototype-based approach, called the Theory of Norms and Exploitations (TNE), the first step is identifying the phraseological patterns with which each word is associated. Meanings are then associated with patterns, rather than with isolated words. Words are highly ambiguous, but patterns are mostly unambiguous. \n Patterns cannot be identified by valency alone, but require statistical analysis and semantic typing of collocates. For example, (1) blowing up a bridge and (2) blowing up a balloon activate different meanings of blow up. But how many other contexts have the same effect on the meaning of the phrasal verb? Relevant members of the lexical set for (1) include building, factory, house, hotel, etc. Such lexical sets provide a basis for machine learning and text processing. \n Authentic uses of words are classified either as normal components of a pattern or as exploitations of norms. For example, “blowing up a condom” is not normal, but exploits (2). Creative metaphors are also exploitations.
Abstract This paper presents an analysis of a sample of intentional deviations from the typical stress pattern of German words. These deviations are described as stress shifts in which the main stress is in a different position to the norm. This process is optional, mainly found in media speech and used for emphatic purposes. All stress shifts involve an interchange of primary and secondary stress, thereby demonstrating their sensitivity to a prosodic-similarity constraint. Stress retractions by far outnumber stress advancements, which can be jointly explained by a probabilistic association of the main stress and the word-initial position in language structure and an anticipatory bias in the language production system. Stress shifts show a strong overrepresentation of adjectives because this word class codes evaluative aspects most naturally and it is evaluations that speakers prefer to emphasize. From a social-psychological perspective, stress shifts are claimed to be a means by which speakers may boast their knowledge and, from a rhetorical perspective, a strategy of making the event being talked about more spectacular. Stress shifts are minority patterns in the sense that the constraints on them are so strong that only relatively few lexical items are eligible. This raises the issue of what speakers do with those items which they wish to emphasize but which do not lend themselves readily to stress shifting. Whether they turn to alternative means of expression or whether they leave their intentions unexpressed remains to be determined.
Semantic intrusions are inappropriate responses frequently observed in patients with Alzheimer's disease. They belong to the same category as the words to be remembered, but their prototypic value remains largely unexplored. The prototype is the most representative word in a particular lexical category. The prototypic value is measured according to different criteria: written and oral lexical frequency, frequency of use, degree of typicality, degree of familiarity and rank of quotation. The objective of the study was to evaluate the prototypic value of intrusions produced by 17 Alzheimer's patients with mild to severe dementia, during the cued recall of the Grober & Buschke procedure (RL/RI 16 items). The prototypic value was compared to the categorial norms provided by 1) 17 control subjects and 2) the lexical database 'Lexique 3'. The results show that intrusions had a significantly higher prototypic value than targeted items. The prototypic value increased with the progression of the disease, and according to the evaluation criteria used. Thus with the criteria 'frequency of use', 'degree of typicality' and 'degree of familiarity,' the prototypic value increased exponentially with the severity of dementia. In contrast, in spite of the development of the pathology, the prototypic value decreased when assessed by the criteria of 'rank of quotation', and 'lexical frequency' (oral and written). In conclusion, the qualitative analysis of the prototypic value of intrusion errors in Alzheimers opens up new clinical and methodological considerations. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
Clinical interviews are a powerful method for assessing students’ knowledge and conceptual development. However, the analysis of the resulting data is time-consuming and can create a “bottleneck” in large-scale studies. This article demonstrates the utility of computational methods in supporting such an analysis. Thirty-four 7th-grade student explanations of the causes of Earth’s seasons were assessed using latent semantic analysis (LSA). Analyses were performed on transcriptions of student responses during interviews administered, prior to (n = 21) and after (n = 13) receiving earth science instruction. An instrument that uses LSA technology was developed to identify misconceptions and assess conceptual change in students’ thinking. Its accuracy, as determined by comparing its classifications to the independent coding performed by four human raters, reached 90%. Techniques for adapting LSA technology to support the analysis of interview data, as well as some limitations, are discussed.
Stanley Kubrick's 2001: A Space Odyssey (1968) has invited an army of commentators and probably encouraged the publication of Arthur C. Clarke's more discursive of the same name shortly after the movie release in April 1968. However, the existing critical discourse on 2001 rarely foregrounds the importance of Clarke's as an independent work with inherent differences from the movie. In fact major science fiction film scholars such as Vivian Sobchak (in Screening Space), Scott Bukatman (in Terminal Identity), and J. P Telotte (in Replications) do not even mention Clarke's in their discussions about the film. Both the movie and the originated in Clarke's short story Sentinel (1948), but Sentinel merely foreshadows the complex conceptual scopes of the works that developed from it. The general critical stance regarding 2001 is a somewhat linear one--from Sentinel to Kubrick's film and then to the novelization of the film by Clarke. Early commentators such as Jeremy Bernstein, Stanley Kauffmann, and Jerome Agel even regarded Clarke's as an explanation of the film, a view which is echoed to some extent by critics like Robert Kolker even in 2006. (1) Again, commentators like David Patterson and Zoe Sofia seem to acknowledge the difference between the and the film and yet end up appropriating the to explain the film. (2) However, a close comparative examination of the and the film clearly shows that Clarke's is neither an explanation nor a novelization of the film but a work existing independently. While Clarke's is rooted directly in the tradition of hardcore science fiction, Kubrick's film subverts all the norms of traditional films to create something unique. On the one hand, Clarke exploits the conventional device of science fictional discourse to contemplate the theme of the existence of higher forms of intelligence in the universe. On the other hand, Kubrick employs a method similar to the transcendental style to bring about an ineffable quality that gives the film a quasi-religious air of mystery. This article contends that though they deal with the same theme, the film and the are the products of two completely different media and should be seen as such. Unlike the common screen adaptations or novelizations, the film and the were created simultaneously; they both function independently of one another, each with its own unique structures, themes, and significance. In Novels into Films (1957), George Bluestone observes that novel and film are both organic--in the sense that aesthetic judgments are based on total ensembles which include both formal and thematic conventions (137). But he also points out that and film are two completely different media, with limits and advantages peculiar to their forms. The aim of a successful film adaptation should not be merely to turn a into a moving version of words on the pages; rather, this is precisely the thing that can never be done. A film and a literary text operate in two distinctly different ways. Suparno Banerjee spells out this concern very clearly: A film is a photo text, a text containing both the visual image and the sound, while the latter [literature] works with words [and ideas] which arouse images but not in the cinematic sense. John Hartley [...] uses the term photopoetry to describe the cinema. Through the use of light--photopoetry (light writing)--it creates images. Media like television (far sight), video (I see), and cinema (movement) [...] share the same property of sight or visual quality [...]. Compared to these audio-visual experiences, literature is, in a sense, an extra-sensory experience [...]. (154) The eye here acts as an instrument which sends the optical impressions of the lexical symbols on the paper to the brain where the real experience takes place. The letters which combine into words, which then form paragraphs and so on, are really sequences of significations of objects which form a succession of images denoting actions, characters, and so on and raise connotative significances in the brain that then work out their meanings and suggestions. …
Background: The alcohol dehydrogenases (ADH) are widely studied enzymes and the evolution of the mammalian gene cluster encoding these enzymes is also well studied. Previous studies have shown that the ADH1B*47His allele at one of the seven genes in humans is associated with a decrease in the risk of alcoholism and the core molecular region with this allele has been selected for in some East Asian populations. As the frequency of ADH1B*47His is highest in East Asia, and very low in most of the rest of the world, we have undertaken more detailed investigation in this geographic region. Methodology/Principal Findings: Here we report new data on 30 SNPs in the ADH7 and Class I ADH region in samples of 24 populations from China and Laos. These populations cover a wide geographic region and diverse ethnicities. Combined with our previously published East Asian data for these SNPs in 8 populations, we have typed populations from all of the 6 major linguistic phyla (Altaic including Korean-J)
This paper describes the use of two machine learning techniques, naive Bayes and decision trees, to address the task of assigning function tags to nodes in a syntactic parse tree. Function tags are extra functional information, such as logical subject or predicate, that can be added to certain nodes in syntactic parse trees. We model the function tags assignment problem as a classification problem. Each function tag is regarded as a class and the task is to find what class/tag a given node in a parse tree belongs to from a set of predefined classes/tags. The paper offers the first systematic comparison of the two techniques, naive Bayes and decision trees, for the task of function tags assignment. The comparison is based on a standardized data set, the Penn Treebank, a collection of sentences annotated with syntactic information including function tags. We found out that decision trees generally outperform naive Bayes for the task of function tagging. Furthermore, this is the first large scale evaluation of decision trees based solutions to the task of functional tagging.
Stereotypes regarding social status lead to the categorization of individuals as belonging to high or low social-status groups, based on little information, such as looks or possession of certain traits. The present study examined the relative effect of looks and musical preference on the inference of other traits relating to high and low social status. Seventy participants were asked to rate photos of eight individuals (four males and four females). Compatible and incompatible pairing of high- and low-status looks and liking for high- and low-status music were created. Findings show that more positive traits were attributed to females, high-status looking individuals and individuals with a preference for high-status music. An interaction between looks and music status was found in which liking for low-status music lowered evaluations in high-status looking individuals, but liking for high-status music did not affect evaluations of low-status looking individuals. Participants' own musical preference did not consistently affect ratings of photographed individuals.
Abstract This paper is a project report of the lexi-cographic Internet portal OWID, an Online Vocabulary Information System of German which is being built at the In-stitute of German Language in Mann-heim (IDS). Overall, the contents of the portal and its technical approaches will be presented. The lexical database is structured in a granular way which al-lows to extend possible search options for lexicographers. Against the back-ground of current research on using elec-tronic dictionaries, the project OWID is also working on first ideas of user-adapted access and user-adapted views of the lexicographic data. Due to the fact that the portal OWID comprises diction-aries which are available online it is pos-sible to change the design and functions of the website easily (in comparison to printed dictionaries). Ideas of implement-ing user-adapted views of the lexico-graphic data will be demonstrated by us-ing an example taken from one of the dictionaries of the portal, namely elexiko.
The dual process theory proposes that evaluative conditioning is a form of learning distinct from Pavlovian conditioning and that it displays different functional characteristics such as not being subject to modulation. However, when assessed online as opposed to post-experimentally, modulation of evaluative conditioning by context change has been found in a contingency reversal procedure. Reversal of evaluative learning was found to be faster when trained in a different context rather than in the original training context. The present study addressed the question whether context change or instructions would affect the rate of reversal of evaluative learning and whether reversal learning would accelerate across repetitions. A picture-picture paradigm was used to expose participants to CS-US pairs and contingency was reversed three times during the experiment. Participants were required to provide online causal judgements and valence ratings after each set of 10 training trials. Context change, but not instructions, displayed a trend in affecting reversal of evaluative learning with participants displaying faster learning on trials immediately subsequent to contingency reversal. Instructions affected the reversal of contingency judgements. There was no evidence of acceleration across repetitions for either measure or manipulation.
In this paper we propose a rule-based approach to extract dependency and grammatical relations from the Venice Italian Treebank (VIT) (Delmonte et al., 2007) with bracketed tree structure. To our knowledge, the only dependency annotated corpus for Italian available is the Turin University Treebank (Lesmo et al., 2002), which has 25,000 tokens and is about 1/10 of VIT. As manual corpus annotation is expensive and time-consuming, we decided to exploit an existing constituency-based treebank, the VIT, to derive dependency structures with lower effort. After describing the procedure to extract heads and dependents, based on a head percolation table for Italian, we introduce the rules adopted to add grammatical relation labels. To this purpose, we manually relabeled all non-canonical arguments, which are very frequent in Italian, then we automatically labeled the remaining complements or arguments following some syntactic restrictions based on the position of the constituents w.r.t to parent and sibling nodes. The final section of the paper describes evaluation results, carried out in two steps, one for dependency relations and one for grammatical roles. Since results are promising, we plan to use the dependency treebank to train a dependency-based parser and eventually a semantic role labelling system. 1. The source corpus
Recently, most of the research in NLP has concentrated on the creation of applications coping with textual entailment. However, there still exist very few resources for the evaluation of such applications. We argue that the reason for this resides not only in the novelty of the research field but also and mainly in the difficulty of defining the linguistic phenomena which are responsible for inference. As the TSNLP project has shown test suites provide optimal diagnostic and evaluation tools for NLP applications, as contrary to text corpora they provide a deep insight in the linguistic phenomena allowing control over the data. Thus in this paper, we present a test suite specifically developed for studying inference problems shown by English adjectives. The construction of the test suite is based on the deep linguistic analysis and following classification of entailment patterns of adjectives and follows the TSNLP guidelines on linguistic databases providing a clear coverage, systematic annotation of inference tasks, large reusability and simple maintenance. With the design of this test suite we aim at creating a resource supporting the evaluation of computational systems handling natural language inference and in particular at providing a benchmark against which to evaluate and compare existing semantic analysers. 1.
In this paper, we present the Web-based resource sharing system KnownStyleNoLife, which allows users explicitly annotate fashion-related images. KnownStyleNoLife harnesses human power and collects image metadata such as object locations, object labels, image rating and semantic relationships among images. Metadata of that type are invaluable as it is difficult for ordinary computer software to extract equivalent metadata from the Web. Acquiring image metadata such as the type and location of objects in images requires a computer to use machine learning techniques, needing training with sample images and Web search techniques, with the outcome that only limited image metadata are extracted. Furthermore, the semantic image relationship metadata is based upon peoplepsilas image perception, hence user feedback is required to acquire it. KnownStyleNoLife provides a social value to users in return for their explicit annotations. It is a novel approach to harness human power to acquire relevant image metadata.
To determine how differences in emotion representation and/or inhibitory ability affect adolescents’ responses to emotion words, 13-yr and 16-yr olds, as well as adults, were compared on the processing of emotion-laden and neutral words. Word ratings revealed that 16-yr olds tended towards perceiving all words as more arousing than did adults, irrespective of valence. Also, they rated words more negatively than 13-yr olds. Performance on an Affective Simon task revealed a marked incongruency effect only for 13-yr olds (and then only for negative words) but not for 16-yr olds (who responded fastest) or adults. Performance on a sustained attention task confirmed the expected age-related increase in inhibitory ability and a concomitant increase in response latencies. Our conclusions are two-fold. First, there are age-related differences in lexical representation which appear more marked for 16-yr olds. Second, 16-yr olds are more reactive, irrespective of the emotional content they are processing, yet appear to control its impact as efficiently as adults.
In this paper we present LXGram, a general purpose grammar for the deep linguistic processing of Portuguese that aims at delivering detailed and high precision meaning representations. LXGram is grounded on the linguistic framework of Head-Driven Phrase Structure Grammar (HPSG). HPSG is a declarative formalism resorting to unification and a type system with multiple inheritance. The semantic representations that LXGram associates with linguistic expressions use the Minimal Recursion Semantics (MRS) format, which allows for the underspecification of scope effects. LXGram is developed in the Linguistic Knowledge Builder (LKB) system, a grammar development environment that provides debugging tools and efficient algorithms for parsing and generation. The implementation of LXGram has focused on the structure of Noun Phrases, and LXGram accounts for many NP related phenomena. Its coverage continues to be increased with new phenomena, and there is active work on extending the grammar's lexicon. We have already integrated, or plan to integrate, LXGram in a few applications, namely paraphrasing, treebanking and language variant detection. Grammar coverage has been tested on newspaper text.
Data Oriented Parsing is a natural language processing model that analyses new input based on past experience. The underlying idea is to extract a set of fragment-probability pairs from a given treebank and use these concrete experiences to construct new utterance analyses. Initially, probabilities were based on the fragments' relative frequency of occurrence. This estimator, however, was soon shown to be biased towards large corpus trees [8] and inconsistent [10]. To alleviate the effects of bias on performance a set of heuristic constraints was put in force. Other estimators addressing these issues have since then been proposed. This paper seeks to show that the most commonly used DOP estimators are in fact susceptible to strong size-sensitive bias effects and to present a new estimation algorithm that greatly reduces these effects of bias on performance without complicating the estimation process.
The treebanks that are used for training statistical parsers consist of hand-parsed sentences from a single source/domain like newspaper text. However, newspaper text concerns different subdomains of language use (e.g. finance, sports, politics, music), which implies that the statistics gathered by generative statistical parsers are averages over subdomain statistics. In this paper we explore a method, subdomain instance-weighting, that exploits raw subdomain corpora for introducing subdomain statistics into a state-of-the-art generative parser. We employ instance-weighting for creating an ensemble of subdomain specific versions of the parser, and explore methods for amalgamating their predictions. Our experiments show that subdomain statistics extracted from raw corpora can even improve the quality of the n-best lists of a formidable, state-of-the-art parser.
Text-to-phoneme (TTP) mapping, also called grapheme-to-phoneme (GTP) conversion, defines the process of transforming a written text into its corresponding phonetic transcription. Text-to-phoneme mapping is a necessary step in any state-of-the-art automatic speech recognition (ASR) and text-to-speech (TTS) system, where the textual information changes dynamically (i.e., new contact entries for name dialing, or new short messages or emails to be read out by a device). There are significant differences between the implementation requirements of a text-to-phoneme mapping module embedded into the automatic speech recognition and into the text-to-speech systems: in automatic speech recognition systems the errors of the text-to-phoneme mapping module are tolerated better (leading to occasional recognition errors) than in the text-to-speech applications, where the effect is immediately and in all cases audible. Automatic speech recognition systems typically use text-to-phoneme mapping to lower the footprint (to avoid storing the lexicon), while maintaining quality. The use of text-to-phoneme mapping in the text-to-speech systems is different. In addition to the phonetic information, the text-to-speech systems also need prosodic information to be able to produce high quality speech, which cannot be predicted by text-to-phoneme mapping. Most state-of-the-art text-to-speech systems use explicit pronunciation lexicon, which is aimed at providing the widest possible coverage, in the order of 100K words, with high quality pronunciation information. Because of this reason, text-to-phoneme mapping is typically used as a fall-back strategy, when the system encounters very rare or non-native words and the quality of a ext-to-speech system is indirectly affected by the quality of the grapheme-to-phoneme conversion. Another important issue is the question of training the text-to-phoneme mapping module. The problem of grapheme-to-phoneme conversion is a static one and such a system is trained off-line. The correspondence between the written and spoken form of a language is usually unchanged in the lifetime of an application. So the complexity/speed of the model training is of secondary importance compared to e.g., the speed of convergence or model size.\n\nIn this thesis, the problem of text-to-phoneme mapping using neural networks is studied. One of the main goals of the thesis is to provide a comprehensive analysis of different neural network structures which can be implemented to convert a written text into its corresponding phonetic transcription. Another important target, of this work, is to provide new solutions that improve the performance of the existing algorithms, in terms of convergence speed and phoneme accuracy. Three main neural network classes are studied in this thesis: the multilayer perceptron (MLP) neural network, the recurrent neural network (RNN) and the bidirectional recurrent neural network (BRNN).\n\nDue to their ability of self adaptation, neural networks have been shown to be a viable solution in applications that require modeling abilities. Such an application is the text-tophoneme mapping where the correspondence between letters of a written text and their corresponding phonetic transcription must be modeled.\n\nOne of the main concerns in all practical implementations, where neural networks are used, is to develop algorithms which provide fast convergence of the synaptic weights and in the same time good mapping performances. When a neural network is trained for text-to-phoneme mapping, at every iteration, a letter-phoneme pair is presented to the network such that, the number of letters and the number of training iterations are equal. As a result, fast convergence of the neural network means smaller size of the training dictionary since fast convergence is in fact similar to less necessary training letters1. A fast convergence speed is important in applications where only a small linguistic database is available. Of course, one solution could be to use a small dictionary (with very few words) which is presented at the input of the neural network many times until the convergence of the synaptic weights is reached. In this case the time of training becomes more important. Taking into account these two sides of the convergence speed (the size of the training dictionary and the processing time during training) one can understand the importance of having algorithms that ensure fast convergence of the neural network.\n\nIt is well known that the error back-propagation algorithm which is used to train the MLP neural network, possess sometimes a quite slow convergence (a very large number of iterations required to reach the stability point). In order to increase the convergence speed two novel alternative solutions are proposed in this thesis: one using an adaptive learning rate in the training process and another which is a transform domain implementation of the multilayer perceptron neural network. The computational complexity of the two proposed training algorithms is slightly higher than the computational complexity of the error back-propagation algorithm but the number of training iterations is highly reduced. Due to this fact, although the three algorithms might have the same training time, the novel algorithms necessitate smaller training dictionary.\n\nDue to the limitations of the processing power that usually are encountered in real devices, another very important requirement for a text-to-phoneme mapping system is to have low computational and memory costs. In the case of text-to-phoneme mapping systems based in neural networks, the computational complexity is mainly linked to the mathematical complexity of the training algorithm as well as to the number of the synaptic weights of the neural network. Memory load is due to the number of synaptic weights of the neural network which must be stored.\n\nTaking into account all these limitations and implementation requirements, in this thesis, several neural network structures with different number of synaptic weights and trained with various training algorithms, are studied. The modeling capability of the neural networks is addressed, which is translated in the text-to-phoneme mapping case into the phoneme accuracy. Different neural network structures, training algorithms and network complexities are analyzed also from this point of view. As a remark here, we mention that input letter encoding plays a very important role in the phoneme accuracy of the grapheme-to-phoneme conversion system. This is why special attention has been paid to the comparative analysis of the performances (in terms of phoneme accuracy) obtained with several orthogonal and non-orthogonal encoding of the input letters.\n\nThe thesis is structured into four main parts. Chapter 1 brings the reader into the world of text-to-phoneme mapping. In Chapter 2 several different neural network structures and their corresponding training algorithms are described and two new training algorithms are introduced and analyzed. In Chapter 3 the experimental results, for the problem of monolingual text-to-phoneme mapping, obtained with the neural networks described in Chapter 2 are shown. Chapter 4 is dedicated to the problem of bilingual grapheme-to-phoneme conversion and Chapter 5 concludes the thesis.
MonaSearch is a new powerful query tool for linguistic treebanks. The query language of MonaSearch is monadic second-order logic, an extension of first-order logic capable of expressing probably all linguistically interesting queries. In order to process queries efficiently, they are compiled into tree automata. A treebank is queried by checking whether the automaton representing the query accepts the tree, for each tree. Experiments show that even complex queries can be executed very efficiently. The tree automaton toolkit MONA is used for the computation of the automata.
Welcome to the ACL Workshop on Parsing German, the first of what we hope will be a long and fruitful series of workshops on this topic. German possesses an interesting set of configurational properties on the syntactic level which make it far less flexible with respect to word order than other free word order languages. Analyses of these properties, which have formed a part of the traditional syntax of German since the early 19th century, only re-entered the mainstream of generative linguistics research within the last twenty years or so. In computational linguistics, however, their realization has varied quite widely: in HPSG-style analyses, multiple parse trees, special constraints on liberation in constraint-based dependency-style analyses, various hybrid deep/shallow approaches, and agnostic parameter estimation over graphs. This variation can also acutely be felt in the annotation of German treebanks. Many corpora have historically elected to annotate only a few of the different senses of the term constituent inherent to German syntax, resulting in standards that make German appear either more like English or more like Czech. The aim of this workshop was to provide a forum for theoretical discussion as well as a shared task, based on the TIGER and TueBa-D/Z German treebanks, for these various approaches to make their case on empirical grounds. This combination we believe to be essential to balancing the considerations of what structure merits learning versus the ease with which it can be learned. Both treebanks are annotated collections of German newspaper text on similar topics. They are annotated with POS, morphology, phrase structure, and grammatical functions. TueBa-D/Z additionally uses topological fields to describe fundamental word order restrictions in German clauses. The treebanks differ significantly in their annotation schemes, however: while TIGER relies on crossing branches to describe long distance relationships, TueBa-D/Z uses pure tree structures with designated labels for long distance relationships. Additionally, the annotation is TIGER is flat on the phrasal level while TueBa-D/Z annotates phrasal structure more hierarchically. A report on the results of this year's shared task can be found in the final paper of these proceedings.
The article is devoted to psychological aspects of communicative influence on professional contact of militia officer, using a district militia officer functions as an example reflecting peculiarities of law-enforcement organs activities as a whole. The role and a place of communicative influence on the process of goals achievement by a militia officer are point out. The results of psychological research are given, confirming the necessity of psycholinguistic norms and rules use by a law-enforcement organs member in order to fulfill his functions successfully
This paper reports on the work carried out developing MedLex+, a medical corpuslexicon workbench for Swedish. This project, which is still under active development, has been going on for some years now within the Department of Swedish language at Goteborg University. At the moment, the workbench incorporates: - an annotated collection of medical texts-including 20 million tokens and 45,000 documents, - a number of language processing software programs, including tools for collocation extraction, compound segmentation and thesaurus-based semantic annotation, and - a lexical database of medical terms-containing 5,000 medical entries. MedLex+ is a multifunctional lexical resource due to a structural design and content which can be easily queried. The medical workbench is intended to support lexicographers compiling lexicons and also lexicon users more or less initiated in the medical domain. MedLex+ can also assist researchers working on either lexical semantics or natural language processing (NLP) applications with focus on medical language. The linguistically and semantically annotated medical texts in combination with a set of smart queries turn the corpora into a rich repository of semasiological and onomasiological knowledge about medical terms and their linguistic, lexical and pragmatic properties. These properties are recorded in the lexical database with a cognitive profile. The MedLex+ workbench seems to offer a constructive help in many different lexical tasks.
Morphological processes in Semitic languages deliver space-delimited words which introduce multiple, distinct, syntactic units into the structure of the input sentence. These words are in turn highly ambiguous, breaking the assumption underlying most parsers that the yield of a tree for a given sentence is known in advance. Here we propose a single joint model for performing both morphological segmentation and syntactic disambiguation which bypasses the associated circularity. Using a treebank grammar, a data-driven lexicon, and a linguistically motivated unknown-tokens handling technique our model outperforms previous pipelined, integrated or factorized systems for Hebrew morphological and syntactic processing, yielding an error reduction of 12% over the best published results so far. 1
Abstract In this paper, I plan to tackle the complex problem of the use and exploitation of bilingual lexical resources available in machine-readable form. The reusability of lexical resources has indeed attracted a lot of attention in the past few years but NLP researchers have tended to concentrate mainly on monolingual English learners’ dictionaries, somewhat neglecting bilingual dictionaries. The less structured format of the magnetic tapes of the latter is probably partly responsible for this lack of interest. The reluctance of publishers to distribute the machine-readable versions of their bilingual dictionaries has also contributed to the concentration of efforts on the exploitation of monolingual (and predominantly English) machinereadable dictionaries (MRDs). However, it has to be admitted, as Atkins and Levin (1991: 255) point out, that “the explicit treatment accorded to restrictions on subjects/objects of verbs in dictionaries for the foreign learner (i.e. bilingual dictionaries) renders such works a valuable source of material for the semi-automatic construction of a lexical database”. In this paper, I wish to describe the construction of a lexical-semantic database from the computerized version of the Collins–Robert English–French dictionary (Atkins and Duval 1978). I will pay special attention to the retrieval programs which make it possible to readily extract the collocational and thesauric information it contains. The emphasis will also be laid on the manual lexicographical work which was required in order to enrich the database with lexical-semantic information based on Mel’čuk’s descriptive apparatus of lexical functions (Mel’čuk et al. 1984/1988/1992). Attention will also be paid to potential exploitations of this bilingual database, ranging from applications in a word sense disambiguation or translation selection perspective to the integration of the lexical database (LDB) into a series of corpus-based tools for collocation extraction, using the dictionary and its lexical-semantic information as an external resource linked to corpus query tools.
Abstract This paper offers a model to explain the general observation that lexical items are more often borrowed from a higher status language into a lower status one, than visa versa. Material from Lahore, Pakistan, shows that in casual speech among plurilinguals codeswitching is the norm. In formal contexts, in which there is attention to proper language, educated speakers filter out features which are not part of the standard language. Constraints on language and education in the hierarchical social structure withhold from most speakers of the lower status languages the knowledge necessary to evaluate their own speech in this way, thus allowing features of other languages to become established in their language.
Writing Like Music: Luciano Berio, Umberto Eco and the New Avant-Garde Florian Mussgnug (bio) Die Dichtung des Lyrikers kann nichts aussagen, was nicht in der ungeheuersten Allgemeinheit und Allgültigkeit bereits in der Musik lag, die ihn zur Bilderrede nötigte. Der Weltsymbolik der Musik ist eben deshalb mit der Sprache auf keine Weise erschöpfend beizukommen. (The poems of the lyrist can express nothing that did not already lie hidden in that vast universality and absoluteness of the music that compelled him to figurative speech. Language can never adequately render the cosmic symbolism of music). Friedrich Nietzsche1 Powerful new influences on a shared artistic imagination and creative practice cannot always be traced to a single, foundational event. Luciano Berio and Umberto Eco’s collaboration at the Studio di fonologia musicale, however, appears to be precisely such an event: an extraordinary encounter between two ambitious and creative young men with important consequences for Italian literature and music in the second half of the twentieth century. As I hope to show in this contribution, serialism, electronic music, and especially Berio’s experiments with the human voice were important sources of inspiration for some of Italy’s most original and distinguished contemporary writers. From the mid-1950s, poets such as Edoardo Sanguineti, Alfredo Giuliani and Nanni Balestrini looked with great interest to the immediate postwar period and to its radical, explosive transformation of modern music, finding there a standard of uncompromising originality and artistic bravery, whose influence can be felt in many of their subsequent declarations regarding the subversive power of poetry. Like their musical precursors in Paris and New York – Pierre Boulez and John Cage – Sanguineti and his peers saw themselves as heirs to the cultural [End Page 81] wealth of earlier European avant-garde movements, but also as members of a new generation, untarnished by the compromises that had been forced on many artists during the years of dictatorship and war.2 Italian experimental literature, like modern music, prided itself on its sense of freshness, exhibited confidence and iconoclastic zeal, and took delight in what Luciano Berio called the ‘liberating effect’ and the ‘sacrificial and somehow clownish impulse’ of avant-garde culture.3 Optimism and the demand for a radical renewal of the arts were also at the heart of Umberto Eco’s influential study Opera aperta (1962), a book that was soon adopted by Italy’s neoavanguardia as its unofficial manifesto.4 Ranging from experimental literature to ‘informal’ painting, from Husserl to Heisenberg, and from non-Euclidean geometry to serial music, Eco’s ambitious investigation conveys an interdisciplinary interest and a sense of intellectual excitement that were characteristic of many artistic circles of the 1950s. Despite its unusually wide scope, however, Eco’s enquiry into ‘openness’ appears particularly pertinent to the methods and concerns of contemporary art: anti-realist prose fiction, computer-generated poetry, serialism and electronic music. Although Eco is primarily concerned with literature, his book opens with a chapter on post-Weberian music, in which the concept of openness is discussed in relation to the works of Karlheinz Stockhausen, Henri Pousseur, Pierre Boulez and Luciano Berio. ‘Openness’ and its related attributes –ambiguity, indeterminacy, discontinuity and polyvalence – are explained by Eco as ‘structural homologies’ (‘analogie di struttura’), which can be traced across different historical periods and in various forms of artistic expression.5 For the poets of Italy’s neoavanguardia, Eco’s emphasis on structural similarity prompted a new way of understanding the analogies between literature and music. During the early 1960s, musicians like Boulez and Berio came to be seen as more than just examples of a successful emancipation from obsolete artistic conventions: their concern with automatism, chance composition and ‘pure form’ also made them important models for a radical renewal of verbal expression.6 This is particularly evident in the neoavanguardia’s efforts to create a non-referential poetic language, which was supposed to provide the foundations for an ‘authentically critical art’ outside ‘the boundaries of bourgeois normality, namely its ideological and linguistic norms’.7 As an influential historian of Italian literature has recently shown, Italy’s new avant-garde was primarily motivated by theoretical demands for a literature without logical and semantic articulation...
Abstract. The paper addresses a problem of extraction of semantic information from Czech texts from the Web. The method described in this paper exploits existing linguistic tools created originally for a syntactically annotated corpus, Prague Dependency Treebank (PDT 2.0). We are working on development of a system which captures text of web-pages, annotates it linguistically by linguistic tools, extracts data and interprets the extracted data semantically in terms of web ontologies. The proposed extraction method is based on extraction rules – tree queries, which are adopted from the Netgraph application. Semantic interpretation of these rules provides semantics of the extracted data. We present some initial experiments in the domain of reports of traffic accidents.
This paper describes a study of the levels at which different rhetorical relations occur in rhetorical structure trees. In a previous empirical study (Williams and Reiter, 2003) of the RST-DT (Rhetorical Structure Theory Discourse Treebank) Corpus (Carlson et al., 2003), we noticed that certain rhetorical relations tended to occur more frequently at higher levels in a rhetorical structure tree, whereas others seemed to occur more often at lower levels. The present study takes a closer look at the data, partly to test this observation, and partly to investigate related issues such as the relative complexity of satellite and nucleus for each type of relation. One practical application of this investigation would be to guide discourse planning in Natural Language Generation (NLG), so that it reflects more accurately the structures found in documents written by human authors. We present our preliminary findings and discuss their relevance for discourse planning.
An improved chart parser based on active edges sharing the leftmost common elements is presented. After analyzing the mechanism of avoiding redundant work in the traditional chart parsing algorithm, the inefficient treatment on active edges possessing the same leftmost common elements was discovered. Then a new presentation of the active edge was proposed to share the same leftmost elements, and thus an improved chart parser was realized with great decrease of generated active edges. The experimental results on Chinese Treebank show that the improved chart parser significantly outperforms the packed chart parser in terms of both speed (about 10 times faster) and space consumption.
Foreign researchers have made great achievements in annotating English text structures with Rhetorical Structure Theory(RST),which provides profound implications for Chinese text annotation.However,there are many differences between Chinese texts and English ones.In fact,Chinese sentence group theory can function as well as RST Theory in annotating Chinese texts.Firstly,the basic framework of RST is quite similar to that of Chinese sentence group theory;secondly,RST theory is less adaptable to Chinese than to English as its analysis values clauses and conjunctions,which are not so salient in Chinese;lastly,texts can be found in Qinghua Treebank whose sentence groups have been marked.
Abstract Self-deception is an important construct in social, personality, and clinical literatures. Although historical and clinical views of self-deception have regarded it as defensive in nature and operation, modern views of this individual difference variable instead highlight its apparent benefits to subjective mental health. The present four studies reinforce the latter view by showing that self-deception predicts positive priming effects, but not negative priming effects, in reaction time tasks sensitive to individual differences in affective priming. In all studies, individuals higher in self-deception displayed stronger positive priming effects, defined in terms of facilitation with two positive stimuli in a consecutive sequence, but self-deception did not predict negative priming effects in the same tasks. Importantly, these effects occurred both in tasks that called for the retrieval of self-knowledge (Study 1) and those that did not (Studies 2–4). This broad pattern supports substantive views of self-deception rather than views narrowly focused on self-presentation processes. Implications for understanding self-deception are discussed. Acknowledgement The authors acknowledge support from NIMH (MH 068241). Notes 1We also performed parallel analyses on the rating means from all studies. Study 1 involved self-judgements of emotion. We therefore thought it likely that self-deception would predict ratings in the task. Indeed, there were main effects of Self-Deception on emotion ratings, both for positive targets, F(1, 18) = 6.16, p<.05, and for negative targets, F(1, 18) = 6.09, p<.05. That is, individuals high in self-deception reported more intense positive emotions (Ms = 3.23 vs. 3.99) and less intense negative emotions (Ms = 2.70 vs. 2.01), relative to individuals low in self-deception. However, Studies 2–4 used affective rating tasks of low self-relevance, and thus we thought it less likely that self-deception would predict ratings in these tasks. Indeed, there were no relations along these lines, ps>.10. Priming effects on ratings, and possible interactions by self-deception, were weak and inconsistent across studies. 2Contact the first author for a list of stimuli. 3Note that these are relatively long judgement times. What is consistent with Studies 1–3 is that a differentiated rating task was used, which would somewhat necessarily slow processing speed (Fazio, 1990). However, this is viewed as beneficial for present purposes as longer processing times have produced stronger and more robust priming effects (e.g., Hines et al., 1996; Joordens & Becker, 1997). Judgement times were slower in Study 4 than in Studies 1–3 and this is attributed to a more differentiated scale (1–8) as well as elimination of the two-response aspect of the procedures used in the earlier studies. The evaluations assessed here clearly involved time and deliberation. However, priming of the responses, we believe, is reliant on the sorts of spreading activation processes shown to be involved in the continuous priming task (de Mornay Davies, 1998; McNamara & Altarriba, 1988; Shelton & Martin, 1992).
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This paper discusses a framework for development of bilingual and multilingual comprehension assistants and presents a prototype implementation of an English-Bulgarian comprehension assistant. The framework is based on the application of advanced graphical user interface techniques, Word-Net and compatible lexical databases as well as a series of NLP preprocessing tasks, including POS-tagging, lemmatisation, multiword expressions recognition and word sense disambiguation. The aim of this framework is to speed up the process of dictionary loop-up, to offer enhanced look-up functionalities and to perform a context-sensitive narrowing-down of the set of translation alternatives proposed to the user.
Conventional n-best reranking techniques often suffer from the limited scope of the n-best list, which rules out many potentially good alternatives. We instead propose forest reranking, a method that reranks a packed forest of exponentially many parses. Since exact inference is intractable with non-local features, we present an approximate algorithm inspired by forest rescoring that makes discriminative training practical over the whole Treebank. Our final result, an F-score of 91.7, outperforms both 50-best and 100-best reranking baselines, and is better than any previously reported systems trained on the Treebank. 1