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16504 papers
The primary data of many experimental studies of animal learning and performance consist of the times at which stimuli and reinforcers were delivered, and the times at which responses occurred. The articles based on most of these studies report selected data, either from some sessions or some animals, or summary measures of the animals’ behavior. The primary data are sufficient to produce any of the selected and summary measures, but the selected and summarized data cannot produce many of the measures used in other experimental reports. It is now feasible to archive the primary data from animal behavior experiments so that they are accessible for others to perform secondary analysis. The value of such secondary analysis of archived data is described with a case study in which rats were trained on three fixed-interval schedules of reinforcement. The full data set may be downloaded fromwww.psychonomic.org/archive/.
In this paper we describe on-going work aimed at creating a dependency-based annotated treebank for the BioMedical domain. Our starting point is the GENIA corpus, which is a corpus of 2000 MEDLINE abstracts, which has been manually annotated for various biological entities, according to the GENIA Ontology. There is an exponential growth of published research in this sector, which makes it difficult even for the experts to follow the recent developments. This creates the need for tools that can automatically process the research literature and extract only relevant information, such as interactions between genes and proteins. In order for these tools to be developed, annotated resources, such as corpora and Treebanks are of fundamental importance. Such resources will support the development of practical domain-specific information extraction tools.
In this paper, a hybrid language model is defined as a combination of a word-based <i>n</i>-gram, which is used to capture the local relations between words, and a category-based stochastic context-free grammar (SCFG) with a word distribution into categories, which is defined to represent the long-term relations between these categories. The problem of unsupervised learning of a SCFG in General Format and in Chomsky Normal Form by means of estimation algorithms is studied. Moreover, a bracketed version of the classical estimation algorithm based on the Earley algorithm is proposed. This paper also explores the use of SCFGs obtained from a treebank corpus as initial models for the estimation algorithms. Experiments on the UPenn Treebank corpus are reported. These experiments have been carried out in terms of the test set perplexity and the word error rate in a speech recognition experiment.
Biomimetic design uses ideas from biological phenomena as inspiration in design. To support biomimetic design, biological analogies are identified by finding instances of functional keywords that describe the engineering problem in biological knowledge in natural-language format. Challenges in using this approach include the identification of keywords, and the quantity and quality of results found. WordNet, a lexical database, is used as a language framework to systematically generate alternative keywords to find matches and analyze the results of searches. Troponyms from WordNet were found to provide better and more plentiful keywords than did synonyms. Due to the potentially large number of matches to keywords, matches are analyzed to facilitate extraction of dominant biological phenomena associated with keywords. This analysis found that words that frequently collocated with keywords tend to be objects of the keyword verb or agents that carry out the actions of the keyword. Furthermore, nouns that are inanimate, e.g., substances, tend to be objects, and nouns that are animate e.g., animals, organs, tend to be agents. Distinguishing frequently collocated words and their relationships to keywords can be used to facilitate identification of biological analogies in natural-language format to support design.Copyright © 2004 by ASME
Function tags are a context-sensitive annotation applied to words and phrases of natural language text, marking their syntactic or semantic role within a larger utterance. As researchers improve results on various other problems in “pure” natural language processing (e.g part-of-speech tagging, parsing), those who work in the more “applied” NLP fields (e.g. question-answering, temporal analysis) are seeking more powerful sorts of linguistic annotation as input for their own systems. Hence, function tags. In the first part of the thesis, I present the problem of function tagging: why it is an interesting problem, who has worked on similar thing, and what exactly I intend to do. I briefly review the function tags of the Penn treebank, and explain the specific metrics by which I will evaluate my work. In the second part of the thesis, I introduce the many features that I will use to train a function tagging system, and then I present some systems that make use of them: one using feature trees, one using decision trees (briefly), and one using perceptron models. For each system, I give a brief historical perspective, an overview of where it has been used before and why I think it will be useful in this task. I will then try a number of feature combinations with interesting properties; and finally, present the best-performing tweaked-out version of that system. Finally, in the third part of the thesis, I bring them all together and discuss the advantages and disadvantages of each system in various situations. More interestingly, I will present an analysis of what features prove to be the most helpful for the different function tagging subtasks. Lastly, I will present a comparison to other systems performing related tasks, and speculate on some interesting future work.
Abstract This study attempted to demonstrate an elevated disgust sensitivity in bulimia nervosa. Eleven bulimic patients and 12 control subjects underwent a functional magnetic resonance imaging (fMRI) study in which they were presented with alternating blocks of 40 disgust‐inducing, 40 fear‐inducing and 40 affectively neutral scenes. Each scene was shown for 1.5 s. After completion of all blocks, affective ratings were then determined. The viewing of the disgusting pictures, which had been rated as highly repulsive by the bulimic females, was associated with an activation of the left amygdala and the occipito‐temporal visual cortex. The subjective and brain‐physiological responses did not differ from those of the healthy control subjects. This held true for the fear‐inducing scenes as well. Thus, bulimic patients are not characterized by an increased global disgust sensitivity and they do not show any indication of an altered central processing of generally disgust and fear‐inducing visual stimuli. Copyright © 2004 John Wiley & Sons, Ltd and Eating Disorders Association.
Concept mapping is a knowledge elicitation technique which stimulates learners to articulate and synthesize their actual states of knowledge during the learning process. Several approaches have been proposed for automating the assessment procedure of learners' concept maps based on an expert's map as a reference point. However, these approaches do not handle cases where learners have misspelled a concept or they have used a synonym or a concept related to the appropriate one. In this paper we present an alternative approach in which the process of the error identification is performed through the use of an expert map and of WordNet which is an electronic lexical database containing semantic relationships between words. This way we handle cases such as misspelled concepts, synonyms and related concepts. After error detection WordNet is also employed for providing the learner with appropriate feedback based on the identified errors, with the intention of helping the learner to correct them.
OBJECTIVE: Transcutaneous electrical nerve stimulation (TENS) is a technique widely used in clinical practice to control pain, although its clinical efficacy remains controversial. Though many mechanisms have been proposed for its analgesic effects, there is a conspicuous lack of experimentally controlled research investigating whether TENS analgesia is related to its effects on the sympathetic nervous system (SNS). METHODS: Using an established psychophysiological paradigm, the present study investigated the effects of high-frequency/low-intensity TENS, low-frequency/high-intensity TENS, and sham TENS on the perception of experimental pain and SNS function in healthy volunteers. Measures of heart rate, digital pulse volume, and skin conductance were recorded during a 20-minute TENS stimulation period and in anticipation of a series of painful electric shocks prior to and following TENS stimulation. Healthy volunteers rated the intensity of the shocks using a 0-10-point verbal pain rating scale. RESULTS: The three TENS conditions failed to differentially effect SNS responses during either the 20-minute TENS treatment period or the shock anticipation periods, and TENS did not affect ratings of pain intensity to the shock stimuli. CONCLUSIONS: While these results may not generalize to acute or chronic pain patients, within the limitations of the present experimental paradigm, no support was found for TENS affecting either SNS function or acute experimental pain perception.
The current research explored the processes that predominate during the anticipation of an emotionally salient event. Experiment 1 (N536), employed three different conditional stimuli followed by pictorial pleasant, unpleasant or neutral unconditioned stimuli. Half the participants were trained with visual CSs, the other half with tactile CSs. In the group trained with visual CSs, startle eyeblinks were larger and faster during CSs that were paired with unpleasant pictures than CSs paired with neutral or pleasant pictures respectively, indicating an affect startle pattern. This linear trend was not found in the group trained with tactile CSs. Experiment 2 (N564) aimed to investigate whether the affective pattern found in the startle data in Experiment 1 could also be found using a behavioural measure of emotion. This time participants’ reaction time during a post-experimental affective priming taskwas used as dependantmeasure to assess the presence of emotional learning. Instead of a simple differential conditioning task, an occasion setting paradigm was employed and participants were trained using either a feature positive or feature negative design with pleasant or unpleasant picture USs. For participants trained with unpleasant USs, valence ratings collected before and after conditioning training suggested the presence of emotional learning, whereas no such pattern was found for participants trained with pleasant USs. These findings were not confirmed in the priming data.
In this paper we describe the construction of a new Japanese lexical resource: the Hinoki treebank. The treebank is built from dictionary definition sentences, and uses an HPSG based Japanese grammar to encode the syntactic and semantic information. We show how this treebank can be used to extract thesaurus information from definition sentences in a language-neutral way using minimal recursion semantics. 1
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The American poetess Emily Dickinson in the 19th century is well-known for her original imagery and unbound language style. Her discarding of the linguistic norms makes her verse darting and whimsical as well as sophisticated to understand. This paper is to interpret the mysterious poetess by means of exploring the linguistic deviations in her poetry. The two deviations that will be focused on are grammatical deviation and graphological deviation.
A novel methodology is presented to enhance Chinese text chunking with the aid of transductive Hidden Markov Models (transductive HMMs),where the chunking is considered as a special tagging problem. An attempt is thus made to utilize it via a number of transformation functions to introduce as much relevant contextual information as possible in model training. These functions enable the models to make use of contextual information to a greater extent and keep away from costly changes of the original training and tagging process. Each of them results in an individual model with certain pros and cons. Through a number of experiments, the best two models are integrated into a significantly better one. The chunking experiments were carried out on the HIT Chinese Treebank corpus, of which the results show that it is an effective approach to the recognition of Chinese chunk, achieving an F score of 8238%.
Abstract. An important aspect of discourse understanding and generation involves the recognition and processing of discourse relations. These are conveyed by discourse connectives, i.e., lexical items like because and as a result or implicit connectives expressing an inferred discourse relation. The Penn Discourse TreeBank (PDTB) provides annotations of the argument structure, attribution and semantics of discourse connectives. In this paper, we provide the rationale of the tagset, detailed descriptions of the senses with corpus examples, simple semantic definitions of each type of sense tags as well as informal descriptions of the inferences allowed at each level. 1
In this paper we introduce a naive algorithm for nondeterminisctic LTAG derivation tree extrac-tion from the Penn Treebank and the Proposi-tion Bank. This algorithm is used in the EM models of LTAG Treebank Induction reported in (Shen and Joshi, 2004). Given the trees in the Penn Treebank with PropBank tags, this algorithm generates shared structures that al-low efficient dynamic programming in the EM models. 1
We investigated subjective and hemodynamic responses towards disgust-inducing, fear-inducing, and neutral pictures in a functional magnetic resonance imaging study. Within an interval of 1 week, 24 male subjects underwent the same block design twice in order to analyze possible response changes to the repeated picture presentation. The results showed that disgust-inducing and fear-inducing scenes provoked a similar activation pattern in comparison to neutral scenes. This included the thalamus, primary and secondary visual fields, the amygdala, the hippocampus, and various regions of the prefrontal cortex. During the retest, the affective ratings hardly changed. In contrast, most of the previously observed brain activations disappeared, with the exception of the temporo-occipital activation. An additional analysis, which compared the emotion-related activation patterns during the two presentations, showed that the responses to the fear-inducing pictures were more stable than the responses to the disgust-inducing ones.
In this paper we address the following questions from our experience of the last two and a half years in developing a large-scale corpus of Arabic text annotated for morphological information, part-of-speech, English gloss, and syntactic structure: (a) How did we 'leapfrog' through the stumbling blocks of both methodology and training in setting up the Penn Arabic Treebank (ATB) annotation? (b) How did we reconcile the Penn Treebank annotation principles and practices with the Modern Standard Arabic (MSA) traditional and more recent grammatical concepts? (c) What are the current issues and nagging problems? (d) What has been achieved and what are our future expectations?
Here, we study the design of domain lexicons and address the problems of lexical knowledge representation and linking between different knowledge sources. A domain lexicon contains substantial domain specific vocabularies with associated phonological, morphological, syntactic and semantic/pragmatic information as well as links to general knowledge bases which are rich enough to support knowledge-intensive models for practical NLP systems. We take financial domain as an example to illustrate the representation structures for syntactic and semantic knowledge. In order to suit for both maximal reusability and deep analysis, our domain lexicon is designed with uniform knowledge representation and fine-grain feature encoding. We also address the issues of how to bridge the gaps between coarse-grain general lexicons and fine-grain domain lexicons.
Rating agencies' track record is good in developed countries but poor in emerging economies. Why? Given the almost-monopolistic structure of the industry, we conjecture that agencies might underinvest in information gathering. We propose an indicator quantifying the agencies' effort to gather information and assess whether greater effort affects rating levels. We detect: (i) absolute underinvestment for non-OECD sovereigns (less effort in spite of greater opaqueness); (ii) relative underinvestment for non-OECD firms compared with OECD ones (though the former receive a larger effort, more intense effort boosts firm ratings in non-OECD countries while depressing them in OECD countries).
In the design of a Multilingual Lexical Database, one of the biggest problems is constituted by conceptual mismatches between languages, and the resulting matter of lexical gaps. Lexical gaps concern words for which there is no direct translation in a target language, but which nonetheless need to receive a translation within the system. In this article, it will be shown that the various possible ways of dealing with these lexical gaps can be classified in four basic groups. Using the SIM<it>u</it>LLDA system as an example (Janssen 2002), the advantages of the structured interlingua approach over the other possibilities will be explained. With the SIM<it>u</it>LLDA set-up, it is possible to derive correct lexical definitions for lexical gaps from the lexical database. How this process of “lexical gap filling” works will be shown using a concrete example of a lexical gap: the treatment of the English words <it>river</it> and <it>stream </it>in contrast with the French words <it>fleuve</it> and <it>rivière</it>.
The purpose of this paper is to describe the TuBa-D/Z treebank of written German and to compare it to the independently developed TIGER treebank (Brants et al., 2002). Both treebanks, TIGER and TuBa-D/Z, use an annotation framework that is based on phrase structure grammar and that is enhanced by a level of predicate-argument structure. The comparison between the annotation schemes of the two treebanks focuses on the different treatments of free word order and discontinuous constituents in German as well as on differences in phrase-internal annotation.
This paper is a contribution to the issue -- which has, in the course of the last decade, become critical -- of the basic requirements and validation criteria for lexical language resources in Standard Arabic. The work is based on a critical analysis of the architecture of the DIINAR.1 lexical database, the entries of which are associated with grammar-lexis relations operating at word-form level (i.e. in morphological analysis). Investigation shows a crucial difference, in the concept of 'lexical database', between source program and generated lexica. The source program underlying DIINAR.1 is analysed, and some figures and ratios are presented. The original categorisations are, in the course of scrutiny, partly revisited. Results and ratios given here for basic entries on the one hand, and for generated lexica of inflected word-forms on the other. They aim at giving a first answer to the question of the ratios between the number of lemma-entries and inflected word-forms that can be expected to be included in, or generated by, a Standard Arabic lexical dB. These ratios can be considered as one overall language-specific criterion for the analysis, evaluation and validation of lexical dB-s in Arabic.
The present work falls in the line of activities promoted by the European Languguage Resource Association (ELRA) Production Committee (PCom) and raises issues in methods, procedures and tools for the reusability, creation, and management of Language Resources. A two-fold purpose lies behind this experiment. The first aim is to investigate the feasibility, define methods and procedures for combining two Italian lexical resources that have incompatible formats and complementary information into a Unified Lexicon (UL). The adopted strategy and the procedures appointed are described together with the driving criterion of the merging task, where a balance between human and computational efforts is pursued. The coverage of the UL has been maximized, by making use of simple and fast matching procedures. The second aim is to exploit this newly obtained resource for implementing the phonological and morphological layers of the CLIPS lexical database. Implementing these new layers and linking them with the already exisitng syntactic and semantic layers is not a trivial task. The constraints imposed by the model, the impact at the architectural level and the solution adopted in order to make the whole database ‘speak ’ efficiently are presented. Advantages vs. disadvantages are discussed. 1. Background and Motivations The work described here raises issues in methods, procedures and tools for the reusability, creation, and management of Language Resources (LRs) and has been
OBJECTIVE: To validate a culturally relevant body image instrument among urban African Americans through three distinct studies. RESEARCH METHODS AND PROCEDURES: In Study 1, 38 medical practitioners performed content validity tests on the instrument. In Study 2, three research staff rated the body image of 283 African-American public housing residents (75% women, mean age = 44 years), with the residents completing body image, BMI, and percentage body fat measures. In Study 3, 35 African Americans (57% men, mean age = 42) completed body image measures and evaluated their cultural relevance. RESULTS: In Study 1, 97% to 100% of practitioners sorted the jumbled figures into the correct ascending order. The correlation between the body image figures and the practitioners' weight classifications of the figures was high (r = 0.91). In Study 2, observers arrived at similar ratings of body size with excellent consistency (alpha = 0.95). Ratings of body image were strongly correlated with participant BMI (r = 0.89 to 0.93 across observers and 0.81 for all participants) and percentage of body fat (r = 0.77 to 0.89 across observers and 0.76 for all participants). In Study 3, body image ratings with the new scale were positively correlated with other validated figural scales. The majority of participants reported that figures in the new body image scale looked most like themselves and other African Americans and were easiest to identify themselves with. DISCUSSION: The instrument displayed strong psychometric performance and cultural relevance, suggesting that the scale is a promising tool for examining body image and obesity among African Americans.
This paper argues for the development of parallel treebanks. It summarizes the work done in this area and reports on experiments for building a Swedish-German treebank. And it describes our approach for reusing resources from one language while annotating another language.
We present a novel methodology to enhance Chinese text chunking with the aid of transductive Hidden Markov Models (transductive HMMs, henceforth). We consider chunking as a special tagging problem and attempt to utilize, via a number of transformation functions, as much relevant contextual information as possible for model training. These functions enable the models to make use of contextual information to a greater extent and keep us away from costly changes of the original training and tagging process. Each of them results in an individual model with certain pros and cons. Through a number of experiments, we succeed in integrating the best two models into a significantly better one. We carry out the chunking experiments on the HIT Chinese Treebank corpus. Experimental results show that it is an effective approach, achieving an F score of 82.38%.
We present the architectural design rationale of a Sanskrit computational linguistics platform, where the lexical database has a central role. We explain the structuring requirements issued from the interlinking of grammatical tools through its hypertext rendition.
This paper presents a prosodic phrasing model for Korean to be used in a text-to-speech synthesis (TTS) system. Read text corpora were morpho-syntactically parsed and prosodically labeled following the Penn Korean Treebank (Han, Chunghye, Ko, Eon-Suk, Yi, Heejong, Palmer, M., 2002. Penn Korean Treebank: development and evaluation. In: Proceedings of the 16th Pacific Asian Conference on Language and Computation. Korean Society for Language and Information.) and K-ToBI prosodic labeling conventions (Sun-Ah, J., 2000. K-ToBI (Korean ToBI) labelling conventions. Version 3.1. Available from: URL.), respectively. Decision trees were trained with morpho-syntactic and textual distance features to predict locations of accentual and intonational phrase breaks. Our phrasing model cross-validated on a 300-sentence corpus (6936 words or 21,436 syllables, with an average of 72 syllables or 23 words per sentence) predicted non-breaks with F=92.4% and breaks with F=88.0% (F=72.8% for accentual phrase breaks and F=71.3% for intonational phrase breaks).
OBJECTIVES: To examine affect and physiological stress in frail older adults in response to a voluntary nursing home relocation. DESIGN: Randomized, controlled trial. SETTING: Long-term care facility located within the greater Philadelphia, Pennsylvania, community. PARTICIPANTS: Seventy-seven nursing home residents, aged 65 and over. INTERVENTION: Experimental group residents were relocated to a newly built nursing home facility with a cluster design in the fall of 2001; control group residents were moved after study completion in the spring of 2002. MEASUREMENTS: Mini-Mental State Examination scores, Observed Affect Rating Scale scores, salivary cortisol, blood pressure, and pulse obtained 1 week before moving and 1 week and 4 weeks after moving. RESULTS: Relocated nursing home residents demonstrated significant differences in salivary cortisol and mood from a randomly selected group of residents that had not yet moved. Relocation resulted in significantly higher cortisol levels 1 week after the move (P=.005), followed by a significant decline in afternoon cortisol at 4 weeks after the move (P=.03). Moreover, relocated residents had significantly lower depression and anxiety symptoms and pulse rates than residents who had not yet moved. CONCLUSION: These findings have important implications for planning medical and social services for relocated elderly. Efforts should be made to prepare individuals for the initial stressors associated with relocation, but it also appears that the stress imposed by relocation is time limited and may begin to ease as early as 4 weeks postmove.
Finding definitions in huge text collections is a challenging problem, not only because of the many ways in which defini-tions can be conveyed in natural language texts but also be-cause the definiendum (i.e., the thing to be defined) has not, on its own, enough discriminative power to allow selection of definition-bearing passages from the collection. We have de-veloped a method that uses already available external sources to gather knowledge about the “definiendum ” before trying to define it using the given text collection. This knowledge consists of lists of relevant secondary terms that frequently co-occur with the definiendum in definition-bearing passages or “definiens”. External sources used to gather secondary terms are an on-line enyclopedia, a lexical database and the Web. These secondary terms together with the definiendum are used to select passages from the text collection perform-ing information retrieval. Further linguistic analysis is car-ried out on each passage to extract definition strings from the passages using a number of criteria including the presence of main and secondary terms or definition patterns.
Evolutionary theory predicts that female intrasexual competition will occur when males of high genetic quality are considered to be a resource. It is probable that women compete in terms of attractiveness since this is one of the primary criteria used by men when selecting mates. Furthermore, because hormones influence the mate-selection process, they may also mediate competition. One competitive strategy that women use is derogation--any act intended to decrease a rival's perceived value. To investigate intrasexual competition through derogation, the influence of oestrogen on women's ratings of female facial attractiveness was examined. During periods of high oestrogen, competition, and hence derogation, increased, as evidenced by lower ratings of female facial attractiveness. By contrast, oestrogen levels did not significantly affect ratings of male faces. These findings support the theory of female intrasexual competition with respect to attractiveness.
This paper reports on an ongoing project that uses varied language resources and advanced NLP tools for a linguistic classification task in discourse semantics. The system we present is designed to assign a “situation entity ” class label to each predicator in English text. The project goal is to achieve the best-possible identification of situation entities in naturally-occurring written texts by implementing a robust system that will deal with real corpus material, rather than just with constructed textbook examples of discourse. In this paper we focus on the combination of multiple information sources, which we see as being vital for a robust classification system. We use a deep syntactic grammar of English to identify morphological, syntactic, and discourse clues, and we use various lexical databases for fine-grained semantic properties of the predicators. Experiments performed to date show that enhancing the output of the grammar with information from lexical resources improves recall but lowers precision in the situation entity classification task. 1.
The effects of emotional connotation on emotional Stroop interference in anxiety were examined. First, a classical conditioning paradigm was used in which neutral words and nonwords were paired with either negative or neutral pictures. These conditioned stimuli were then presented in an emotional Stroop paradigm. Finally, participants rated each word and nonword for emotional connotation. The high-anxious group demonstrated significant interference for the nonwords that had been negatively conditioned, and these effects did not dissipate over time. The affective rating data supported the view that nonwords, but not the words had been successfully conditioned in the high-anxious group. This experiment provides evidence for the importance of emotional connotation rather than confounded semantic factors in the emotional Stroop effect.
We describe an approach to two areas of biomedical information extraction, drug development and cancer genomics. We have developed a framework which includes corpus annotation integrated at multiple levels: a Treebank containing syntactic structure, a Propbank containing predicate-argument structure, and annotation of entities and relations among the entities. Crucial to this approach is the proper characterization of entities as relation components, which allows the integration of the entity annotation with the syntactic structure while retaining the capacity to annotate and extract more complex events. We are training statistical taggers using this annotation for such extraction as well as using them for improving the annotation process.
This paper describes a method for conducting evaluations of Treebank and non-Treebank parsers alike against the English language U. Penn Treebank (Marcus et al., 1993) using a metric that focuses on the accuracy of relatively non-controversial aspects of parse structure. Our conjecture is that if we focus on maximal projections of heads (MPH), we are likely to find much broader agreement than if we try to evaluate based on order of attachment. We hope that this method may find wider acceptance and be useful in establishing a generally applicable framework for evaluation in natural language parsing. We employ this method in an evaluation of NLPWin (Heidorn, 2000), a parser developed at Microsoft Research without reference to the Penn Treebank, and, for comparison, the well-known statistical Treebank parser of Charniak (2000). 1.
This paper describes a new, large scale discourse-level annotation project -- the Penn Discourse TreeBank (PDTB). We present an approach to annotating a level of discourse structure that is based on identifying discourse connectives and their arguments. The PDTB is being built directly on top of the Penn TreeBank and Propbank, thus supporting the extraction of useful syntactic and semantic features and providing a richer substrate for the development and evaluation of practical algorithms.
This paper investigates the usefulness of sentence-internal prosodic cues in syntactic parsing of transcribed speech. Intuitively, prosodic cues would seem to provide much the same information in speech as punctuation does in text, so we tried to incorporate them into our parser in much the same way as punctuation is. We compared the accuracy of a statistical parser on the LDC Switchboard treebank corpus of transcribed sentence-segmented speech using various combinations of punctuation and sentence-internal prosodic information (duration, pausing, and f0 cues).