Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
16504 papers
Children adopted from China currently represent the largest group of newly internationally adopted children in the US. An exploratory investigation of the communicative development of six young females adopted at ages 9 to 17 months from China by US families was conducted. Children were followed longitudinally from approximately three months post-adoption to age three years. English language skills were assessed at approximately three-month intervals, detailed communicative analyses were conducted at six months post-adoption, and outcomes were measured at three years of age. Results indicated wide variability in rates of English language development. Phonological, social-communicative, and lexical bases of communication were intact for each child at six months post-adoption. At age three years, four of the children demonstrated speech and language skills within one standard deviation of standardized test norms, one child demonstrated skills above the normal range, and one child's skills were below the normal range. This study provides evidence of the resiliency of children's language learning abilities.
This paper addresses a classical but important problem: The coupling of lexical tones and sentence intonation in tonal languages, such as Chinese, focusing particularly on voice fundamental frequency (F1) contours of speech. It is important because it forms the basis of speech synthesis technology and prosody analysis. We provide a solution to the problem with a constrained tone transformation technique based on structural modeling of the F1 contours. This consists of transforming target values in pairs from norms to variants. These targets are intended to sparsely specify the prosodic contributions to the F1 contours, while the alignment of target pairs between norms and variants is based on underlying lexical tone structures. When the norms take the citation forms of lexical tones, the technique makes it possible to separate sentence intonation from observed F0 contours. When the norms take normative F0 contours, it is possible to measure intonation variations from the norms to the variants, both having identical lexical tone structures. This paper explains the underlying scientific and linguistic principles and presents an algorithm that was implemented on computers. The method's capability of separating and combining tone and intonation is evaluated through analysis and re-synthesis of several hundred observed F0 contours.
Using a speeded lexical decision task, event-related potentials (ERPs), and minimum norm current source estimates, we investigated early spatiotemporal aspects of cortical activation elicited by words and pseudo-words that varied in their orthographic typicality, that is, in the frequency of their component letter pairs (bi-grams) and triplets (tri-grams). At around 100 msec after stimulus onset, the ERP pattern revealed a significant typicality effect, where words and pseudo-words with atypical orthography (e.g., yacht, cacht) elicited stronger brain activation than items characterized by typical spelling patterns (cart, yart). At approximately 200 msec, the ERP pattern revealed a significant lexicality effect, with pseudo-words eliciting stronger brain activity than words. The two main factors interacted significantly at around 160 msec, where words showed a typicality effect but pseudo-words did not. The principal cortical sources of the effects of both typicality and lexicality were localized in the inferior temporal cortex. Around 160 msec, atypical words elicited the stronger source currents in the left anterior inferior temporal cortex, whereas the left perisylvian cortex was the site of greater activation to typical words. Our data support distinct but interactive processing stages in word recognition, with surface features of the stimulus being processed before the word as a meaningful lexical entry. The interaction of typicality and lexicality can be explained by integration of information from the early form-based system and lexicosemantic processes.
DepAnn is an interactive annotation tool for dependency treebanks, providing both graphical and text-based annotation interfaces. The tool is aimed for semi-automatic creation of treebanks. It aids the manual inspection and correction of automatically created parses, making the annotation process faster and less error-prone. A novel feature of the tool is that it enables the user to view outputs from several parsers as the basis for creating the final tree to be saved to the treebank. DepAnn uses TIGER-XML, an XML-based general encoding format for both, representing the parser outputs and saving the annotated treebank. The tool includes an automatic consistency checker for sentence structures. In addition, the tool enables users to build structures manually, add comments on the annotations, modify the tagsets, and mark sentences for further revision.
In this paper, we attempt to automatically annotate the Penn Chinese Treebank with semantic dependency structure. Ini-tially a small portion of the Penn Chinese Treebank was man-ually annotated with headword and semantic dependency re-lations. An initial investigation is then done using a Naive Bayesian Classifier and some handcrafted rules. The results show that the algorithms and proposed approach are effective at determining semantic dependency structure automatically. The Naive Bayesian Classifier makes a good baseline algo-rithm for future research.
This paper evaluates four of the most commonly used, freely available, state-of-the-art parsers on a standard benchmark as well as with respect to a set of data relevant for measuring text cohesion, as one example of a learning technology application that requires fast and accurate syntactic parsing. We outline advantages and disadvantages of existing technologies and make recommendations. Our performance report uses traditional measures based on a gold standard as well as novel dimensions for parsing evaluation. To our knowledge, this is the first attempt to evaluate parsers across genres and grade levels for the implementation in learning technology using both gold standard and directed evaluation methods.
Sentence similarity measures play an increasingly important role in text-related research and applications in areas such as text mining, Web page retrieval, and dialogue systems. Existing methods for computing sentence similarity have been adopted from approaches used for long text documents. These methods process sentences in a very high-dimensional space and are consequently inefficient, require human input, and are not adaptable to some application domains. This paper focuses directly on computing the similarity between very short texts of sentence length. It presents an algorithm that takes account of semantic information and word order information implied in the sentences. The semantic similarity of two sentences is calculated using information from a structured lexical database and from corpus statistics. The use of a lexical database enables our method to model human common sense knowledge and the incorporation of corpus statistics allows our method to be adaptable to different domains. The proposed method can be used in a variety of applications that involve text knowledge representation and discovery. Experiments on two sets of selected sentence pairs demonstrate that the proposed method provides a similarity measure that shows a significant correlation to human intuition
This report explores the question of compatibility between annotation projects including translating annotation formalisms to each other or to common forms. Compatibility issues are crucial for systems that use the results of multiple annotation projects. We hope that this report will begin a concerted effort in the field to track the compatibility of annotation schemes for part of speech tagging, time annotation, treebanking, role labeling and other phenomena.
OBJECTIVE: We examined whether affect ratings predicted regional cerebral responses to high and low-calorie foods. METHOD: Thirteen normal-weight adult women viewed photographs of high and low-calorie foods while undergoing functional magnetic resonance imaging (fMRI). Regression analysis was used to predict regional activation from positive and negative affect scores. RESULTS: Positive and negative affect had different effects on several important appetite-related regions depending on the calorie content of the food images. When viewing high-calorie foods, positive affect was associated with increased activity in satiety-related regions of the lateral orbitofrontal cortex, but when viewing low-calorie foods, positive affect was associated with increased activity in hunger-related regions including the medial orbitofrontal and insular cortex. The opposite pattern of activity was observed for negative affect. CONCLUSION: These findings suggest a neurobiologic substrate that may be involved in the commonly reported increase in cravings for calorie-dense foods during heightened negative emotions.
This paper presents a Constraint Grammar-inspired machine learner and parser, LingPars, that assigns dependencies to morphologically annotated treebanks in a function-centred way. The system not only bases attachment probabilities for PoS, case, mood, lemma on those features' function probabilities, but also uses topological features like function/PoS n-grams, barrier tags and daughter-sequences. In the CoNLL shared task, performance was below average on attachment scores, but a relatively higher score for function tags/deprels in isolation suggests that the system's strengths were not fully exploited in the current architecture.
The thesis presents tools for analysis at analytical and tectogrammatical layers that the Prague Dependency Treebank is based on. The tools for analytical annotation consist of two parsers and a tool for assigning syntactic tags. Although the performance of the parsers is far below that of the state-of-the-art parsers, they both can be considered a certain contribution to parsing, since the methods they are based on are novel. The tool for assigning syntactic tags makes 15% less errors than a tool used for this purpose previously. The tool developed for tectogrammatical annotation is the only one that can currently perform this task in such a breadth. Although other, specialized tools may have a better performance of some of its particular subtasks, my tool makes 29% and 47% less errors for the Czech language than the combination of existing tools for annotating the tectogrammatical structure and deep functors, respectively, which are the core of the tectogrammatical layer. The proposed tools are designed the way they can be used for other languages as well.
The amygdala is closely linked to basal ganglia circuitry and plays a key role in danger detection and fear-potentiated startle. Based on recent findings of amygdalar abnormalities in Parkinson's disease, we hypothesized that non-demented patients with this illness would show blunted reactivity during aversive/unpleasant events, as indexed by diminished emotional modulation of the startle eyeblink response. To test this hypothesis, 23 idiopathic patients with Parkinson's disease and 17 controls viewed standardized sets of aversive, pleasant and neutral pictures for 6 s each. During this time, white noise bursts (50 ms, 95 db) were binaurally presented to elicit startle eyeblink responses, measured from electrodes over the orbicularis oculi. After viewing each picture, subjects provided ratings of valence and arousal. The Parkinson's disease patients were in the early to middle stages of their disease, not demented or depressed, and were tested 'on' dopaminergic medication. The two groups were similar in age, education, gender and cognitive screening status. The control group had larger startle responses when viewing negative, aversive pictures than neutral or pleasant pictures. As predicted, startle enhancement during aversive pictures was significantly muted in the Parkinson's disease patients. This blunting was not due to abnormalities in the mechanics of the startle eyeblink per se. Nor was it related to depression symptoms, medications (psychotropics), or failure to perceive/appreciate the negative meaning of aversive pictures (i.e. normal valence ratings). Reduced startle reactivity in the disease group was related to disease severity (Hoehn-Yahr) and occurred in the context of reduced arousal ratings of aversive pictures. These findings of blunted startle reactivity add to the literature on emotional changes associated with Parkinson's disease. The basis for this muted reactivity is unknown but may involve an amygdala-based translational defect whereby the results of cognitive appraisal are not appropriately transcoded into somato-motor-arousal responses normally associated with an aversive motivational state. This may arise from faulty dopaminergic gating of the amygdala, resulting in 'inhibition' of the amygdala in the manner described by Marowsky et al. (Marowsky A, Yanagawa Y, Obata K, Vogt E. Neuron 2005; 48: 1025-37). More broadly, the findings of muted reactivity to aversive stimuli may reflect a 'bradylimbic' affective disturbance in patients with Parkinson's disease. Future studies are needed to address whether the physiologic blunting observed here might be a useful correlate of apathy.
In this paper, we present a novel approach to combine the outputs of multiple MT engines into a consensus translation. In contrast to previous Multi-Engine Machine \nTranslation (MEMT) techniques, we do not rely on word alignments of output hypotheses, but prepare the input sentence for multi-engine processing. We do this by using a recursive decomposition algorithm that produces simple chunks as input to the MT engines. A consensus translation \nis produced by combining the best chunk translations, selected through majority voting, a trigram language model \nscore and a confidence score assigned to each MT engine. We report statistically significant relative improvements \nof up to 9% BLEU score in experiments (English→Spanish) carried out on an 800-sentence test set extracted from the Penn-II Treebank.
Recently proposed deterministic classifier-based parsers (Nivre and Scholz, 2004; Sagae and Lavie, 2005; Yamada and Mat-sumoto, 2003) offer attractive alternatives to generative statistical parsers. Deterministic parsers are fast, efficient, and simple to implement, but generally less accurate than optimal (or nearly optimal) statistical parsers. We present a statistical shift-reduce parser that bridges the gap between deterministic and probabilistic parsers. The parsing model is essentially the same as one previously used for deterministic parsing, but the parser performs a best-first search instead of a greedy search. Using the standard sections of the WSJ corpus of the Penn Treebank for training and testing, our parser has 88.1% precision and 87.8% recall (using automatically assigned part-of-speech tags). Perhaps more interestingly, the parsing model is significantly different from the generative models used by other well-known accurate parsers, allowing for a simple combination that produces precision and recall of 90.9% and 90.7%, respectively.
We present an automatic approach to tree annotation in which basic nonterminal symbols are alternately split and merged to maximize the likelihood of a training treebank. Starting with a simple X-bar grammar, we learn a new grammar whose nonterminals are subsymbols of the original nonterminals. In contrast with previous work, we are able to split various terminals to different degrees, as appropriate to the actual complexity in the data. Our grammars automatically learn the kinds of linguistic distinctions exhibited in previous work on manual tree annotation. On the other hand, our grammars are much more compact and substantially more accurate than previous work on automatic annotation. Despite its simplicity, our best grammar achieves an F1 of 90.2% on the Penn Treebank, higher than fully lexicalized systems.
Motivationally relevant stimuli have been shown to receive prioritized processing compared to neutral stimuli at distinct processing stages. This effect has been related to the evolutionary importance of rapidly detecting dangers and potential rewards and has been shown to be modulated by the distance between an organism and a faced stimulus. Similarly, recent studies showed degrees of emotional modulation of autonomic responses and subjective arousal ratings depending on stimulus size. In the present study, affective modulation of pictures presented in different sizes was investigated by measuring event-related potentials during a two-choice categorization task. Results showed significant emotional modulation across all sizes at both earlier and later stages of processing. Moreover, affective modulation of earlier processes was reduced in smaller compared to larger sizes, whereas no changes in affective modulation were observed at later stages.
The suitability of computer‐based instruction (CBI) for workers with limited education was evaluated in an Hispanic orchard workforce that reported little computer experience and 5.6 mean years of formal education. Ladder safety training was completed by employees who rated the training highly (effect size [d_gain] = 5.68), and their knowledge of ladder safety improved (d_gain = 1.45). There was a significant increase (p < 0.01) in safe work practices immediately after training (d_gain = 0.70), at 40 days post training (d_gain = 0.87) and at 60 days (d_gain = 1.40), indicating durability. As in mainstream populations, reaction or affective ratings correlated well with utility ratings, but not with behavior change. This demonstrates that an agricultural workforce with limited formal education can learn job safety from CBI and translate the knowledge to work practice changes, and those changes are durable.
The current paper has a twofold objective. On the one hand, it describes the creation and the features of the Szeged Treebank, which is currently the largest manually processed Hungarian textual database serving as a reference material for research in natural language processing. On the other hand, detailed information is given about different experiments that aimed at the automatic recognition of syntactic structures with the use of machine learning algorithms. In order to provide comparable results, we applied methods of different categories, namely a rule-based, a logic and a numeric learner to pre-defined parsing problems. The aforementioned Szeged Treebank was used for the training and the testing of the algorithms.
In this paper we describe the structure and development of the Brandeis Semantic Ontology (BSO), a large generative lexicon ontology and lexical database. The BSO has been designed to allow for more widespread access to Generative Lexicon-based lexical resources and help researchers in a variety of computational tasks. The specification of the type system used in the BSO largely follows that proposed by the SIMPLE specification (Busa et al., 2001), which was adopted by the EU-sponsored SIMPLE project (Lenci et al., 2000). 1.
We present a novel PCFG-based architecture for robust probabilistic generation based on wide-coverage LFG approximations (Cahill et al., 2004) automatically extracted from treebanks, maximising the probability of a tree given an f-structure. We evaluate our approach using string-based evaluation. We currently achieve coverage of 95.26%, a BLEU score of 0.7227 and string accuracy of 0.7476 on the Penn-II WSJ Section 23 sentences of length ≤20.
In this paper, current dependencybased treebanks are introduced and analyzed.The methods used for building the resources, the annotation schemes applied, and the tools used (such as POS taggers, parsers and annotation software) are discussed.
We propose a method for labelling prepositional phrases according to two different semantic role classifications, as contained in the Penn treebank and the CoNLL 2004 Semantic Role Labeling data set. Our results illustrate the difficulties in determining preposition semantics, but also demonstrate the potential for PP semantic role labelling to improve the performance of a holistic semantic role labelling system.
The Hamburg implementation of the Weighted Constraint Dependency Grammar formalism (WCDG) includes an example grammar with comprehensive coverage for written German. This manual is the annotation guideline that was used to define the goals of the grammar and to create the Hamburg Dependency Treebank also published in the course of this project.
Deterministic parsing guided by treebank-induced classifiers has emerged as a simple and efficient alternative to more complex models for data-driven parsing. We present a systematic comparison of memory-based learning (MBL) and support vector machines (SVM) for inducing classifiers for deterministic dependency parsing, using data from Chinese, English and Swedish, together with a variety of different feature models. The comparison shows that SVM gives higher accuracy for richly articulated feature models across all languages, albeit with considerably longer training times. The results also confirm that classifier-based deterministic parsing can achieve parsing accuracy very close to the best results reported for more complex parsing models.
Approximately 60 kinds of lexical relations have been recognized in languages of the world (Grimes & Grimes, 1993). In this paper, I present evidence for a wide range of lexical relations in the Ilokano language. Grimes explains the meaning of lexical relations in terms of the way two words are related but differ in meaning, giving examples such as write and writer, row and rower. I will exemplify some of the types of lexical relations attested in Ilokano: 1) Verbs with an incorporated nominal, e.g. ag-diram'os 'to wash one's face' where the implied noun is 'face'; aginnaw 'wash dishes', implied noun, 'dishes'. There is no word for 'face' in agdiram'os, nor word for 'dishes' in aginnaw. 2) Derived nouns expressing an agentive relation, e.g. from the verb agsugal 'to gamble' the derived noun is mannugal 'gambler', agsurat 'to write', mannurat 'writer'. 3) Reduplication of a noun describing a condition of that noun, e.g. saka 'foot', saka-saka 'barefoot'; ima 'hand', ima-ima 'emptyhanded'. 4) Derived verbs denoting animal vocalization, e.g. aso 'dog', agtaol (phonation) 'to bark', ul'ul'ol (onomatopoeia); 5) Derived verbs denoting a quantum, e.g. sangalilig a sua 'one section of a pomelo'; 6) Complements, e.g. biag ken patay 'life and death'; 7) Derived verbs denoting function, e.g. karayan 'river', agayos 'to flow', sabong flower', agukrad 'to bloom'. I will then show how these derivations are handled in the Ilokano Lexical Database where they are listed making use of the band format.
Linguists use treebanks as resource for collecting evidence of phenomena which cannot be easily recovered from data that is annotated at word level only, this includes collecting quantitative data, getting non-categorical information such as heaviness or finding natural sounding counter examples 1 (e.g. Uszkoreit et al. (1998); Arnold et al. (2000); Bresnan et al. (to appear)) 2. Tools such as TIGERSearch allow us easy access to the encoded information. 3 This poster presents work on the Tübinger Baumbank deutscher Zeitungssprache (Tüba-D/Z). It describes the encoding of coordination phenomena in the treebank and gives a qualitative and quantitative survey. 2 The TüBa-D/Z Treebank It is a corpus of newspaper texts which currently comprises about 22 000 sentences (more than 381 000 tokens) taken from the Wissenschafts-CD of ’die tageszeitung ’ (taz). The annotation combines information on inflectional morphology, part of speech, phrase structure (or rather recursive chunking), grammatical dependencies and topological fields. In addition, it includes marking of named entities and annotation of anaphoric and coreference relations (cf. Hinrichs et al. (2004)).
Transforming syntactic representations in order to improve parsing accuracy has been exploited successfully in statistical parsing systems using constituency-based representations. In this paper, we show that similar transformations can give substantial improvements also in data-driven dependency parsing. Experiments on the Prague Dependency Treebank show that systematic transformations of coordinate structures and verb groups result in a 10% error reduction for a deterministic data-driven dependency parser. Combining these transformations with previously proposed techniques for recovering non-projective dependencies leads to state-of-the-art accuracy for the given data set.
ELSIのSは『社会的』との意味である。しかしながら,医療や医学での社会的問題とは如何なる側面を指すのかはあまり明らかではない。第II報では倫理という概念について議論したが,本稿では『社会的』とは如何なる概念であるかを考える。今回,医療・医学の進歩と市民社会の成立という新機軸(今までには存在しなかった新しい方法や状況)を比較しつつ考察する。どうやらELSIの社会とは,辞書的な社会とはややニュアンスを異にした概念であるようだ。また,市民社会にはそれを支える社会規範より上位に立つ基本的な哲学(本稿では人権尊重と経済的自由主義を取り上げる)が存在するが,医療・医学でのELSIには未だそれに比肩するほどの成熟は見られない。|S of ELSI is the meanig of ”social”. However, it is not clear what ”social” means in medical cares and medicine. We argued about the concept of ethics in the second report. In this reoport we argued about ”social”. And in this report we compared the progression of medical cares and medicine with the formation of civilian society, which are both, what we call innovation. ”Social” of ELSI seems to be the concept that differs from lexical ”social” in a nuance a little somehow or other. In addition, there are basic philosophies (I took up respects of human rights and economic liberalism in this report) in civilian society to support itself, which are in higher rank than in social norms, but ELSI in medical cares and medicine has been immature.
Line drawings are commonly used in perception research. A basic strategy used in such research is to remove portions of the line drawings in order to determine what features of an object are important for recognition. However, it is important to monitor the amount of contour and type of information that are deleted when one is making partially deleted or fragmented objects. With the Image Fragmenting Program, researchers can use random or manual contour deletion strategies to create fragmented objects while controlling for the amount of contour removed from the images.
The movements of newborns have been thoroughly studied in terms of reflexes, muscle synergies, leg coordination, and target-directed arm/hand movements. Since these approaches have concentrated mainly on separate accomplishments, there has remained a clear need for more integrated investigations. Here, we report an inquiry in which we explicitly concentrated on taking such a perspective and, additionally, were guided by the methodological concept of home base behavior, which Ilan Golani developed for studies of exploratory behavior in animals. Methods from nonlinear dynamics, such as symbolic dynamics and recurrence plot analyses of kinematic data received from audiovisual newborn recordings, yielded new insights into the spatial and temporal organization of limb movements. In the framework of home base behavior, our approach uncovered a novel reference system of spontaneous newborn movements.
Abstract Facial masculinity may be used as a cue in female mate choice, as it reflects the success of the male genotype in its developmental environment. Women may maximize reproductive success by using a conditional strategy favoring highly masculine facial features for short‐term relationships and feminized facial features in men for long‐term relationships. Three studies examine reactions to masculinized and feminized male facial composites. Properties of the original composite image affect ratings of critical attributes and the magnitude of the differences in ratings between versions undergoing identical processes of geometric manipulation (Study 1). Both men and women attribute personality, behavior, and mating strategies consistent with predictions derived from the good genes and mating trade‐off hypotheses (Study 2). Participants accurately grouped behavioral tendencies related to high mating effort/risky strategies and high parenting effort/risk adverse strategies and associated mating effort more so with masculinized faces and parenting effort more so with feminized faces (Study 3). These results indicate that male facial masculinity serves as a visual cue for inferring personality and reproductive strategy.
Recent research on causal learning found (a) that causal judgments reflect either the current predictive value of a conditional stimulus (CS) or an integration across the experimental contingencies used in the entire experiment and (b) that postexperimental judgments, rather than the CS's current predictive value, are likely to reflect this integration. In the current study, the authors examined whether verbal valence ratings were subject to similar integration. Assessments of stimulus valence and contingencies responded similarly to variations of reporting requirements, contingency reversal, and extinction, reflecting either current or integrated values. However, affective learning required more trials to reflect a contingency change than did contingency judgments. The integration of valence assessments across training and the fact that affective learning is slow to reflect contingency changes can provide an alternative interpretation for researchers' previous failures to find an effect of extinction training on verbal reports of CS valence.
We identify problems with the Penn Treebank that render it imperfect for syntaxbased machine translation and propose methods of relabeling the syntax trees to improve translation quality. We develop a system incorporating a handful of relabeling strategies that yields a statistically significant improvement of 2.3 BLEU points over a baseline syntax-based system.