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At least 469 records · Page 26Linked to original sources

arXiv1997

A Model of Lexical Attraction and Repulsion

This paper introduces new methods based on exponential families for modeling the correlations between words in text and speech. While previous work assumed the effects of word co-occurrence statistics to be constant over a window of several hundred words, we show that their influence is nonstationary on a much smaller time scale. Empirical data drawn from English and Japanese text, as well as conversational speech, reveals that the ``attraction'' between words decays exponentially, while stylistic and syntactic contraints create a ``repulsion'' between words that discourages close co-occurrence. We show that these characteristics are well described by simple mixture models based on two-stage exponential distributions which can be trained using the EM algorithm. The resulting distance distributions can then be incorporated as penalizing features in an exponential language model.

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arXiv1997

Evaluating Competing Agent Strategies for a Voice Email Agent

This paper reports experimental results comparing a mixed-initiative to a system-initiative dialog strategy in the context of a personal voice email agent. To independently test the effects of dialog strategy and user expertise, users interact with either the system-initiative or the mixed-initiative agent to perform three successive tasks which are identical for both agents. We report performance comparisons across agent strategies as well as over tasks. This evaluation utilizes and tests the PARADISE evaluation framework, and discusses the performance function derivable from the experimental data.

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arXiv1997

Expectations in Incremental Discourse Processing

The way in which discourse features express connections back to the previous discourse has been described in the literature in terms of adjoining at the right frontier of discourse structure. But this does not allow for discourse features that express expectations about what is to come in the subsequent discourse. After characterizing these expectations and their distribution in text, we show how an approach that makes use of substitution as well as adjoining on a suitably defined right frontier, can be used to both process expectations and constrain discouse processing in general.

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arXiv1997

Natural Language Generation in Healthcare: Brief Review

Good communication is vital in healthcare, both among healthcare professionals, and between healthcare professionals and their patients. And well-written documents, describing and/or explaining the information in structured databases may be easier to comprehend, more edifying and even more convincing, than the structured data, even when presented in tabular or graphic form. Documents may be automatically generated from structured data, using techniques from the field of natural language generation. These techniques are concerned with how the content, organisation and language used in a document can be dynamically selected, depending on the audience and context. They have been used to generate health education materials, explanations and critiques in decision support systems, and medical reports and progress notes.

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arXiv1997

Structure and Ostension in the Interpretation of Discourse Deixis

This paper examines demonstrative pronouns used as deictics to refer to the interpretation of one or more clauses. Although this usage is frowned upon in style manuals (for example Strunk and White (1959) state that ``This. The pronoun 'this', referring to the complete sense of a preceding sentence or clause, cannot always carry the load and so may produce an imprecise statement.''), it is nevertheless very common in written text. Handling this usage poses a problem for Natural Language Understanding systems. The solution I propose is based on distinguishing between what can be pointed to and what can be referred to by virtue of pointing. I argue that a restricted set of discourse segments yield what such demonstrative pronouns can point to and a restricted set of what Nunberg (1979) has called referring functions yield what they can refer to by virtue of that pointing.

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arXiv1997

Epistemic NP Modifiers

The paper considers participles such as "unknown", "identified" and "unspecified", which in sentences such as "Solange is staying in an unknown hotel" have readings equivalent to an indirect question "Solange is staying in a hotel, and it is not known which hotel it is." We discuss phenomena including disambiguation of quantifier scope and a restriction on the set of determiners which allow the reading in question. Epistemic modifiers are analyzed in a DRT framework with file (information state) discourse referents. The proposed semantics uses a predication on files and discourse referents which is related to recent developments in dynamic modal predicate calculus. It is argued that a compositional DRT semantics must employ a semantic type of discourse referents, as opposed to just a type of individuals. A connection is developed between the scope effects of epistemic modifiers and the scope-disambiguating effect of "a certain".

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arXiv1997

Centering, Anaphora Resolution, and Discourse Structure

Centering was formulated as a model of the relationship between attentional state, the form of referring expressions, and the coherence of an utterance within a discourse segment (Grosz, Joshi and Weinstein, 1986; Grosz, Joshi and Weinstein, 1995). In this chapter, I argue that the restriction of centering to operating within a discourse segment should be abandoned in order to integrate centering with a model of global discourse structure. The within-segment restriction causes three problems. The first problem is that centers are often continued over discourse segment boundaries with pronominal referring expressions whose form is identical to those that occur within a discourse segment. The second problem is that recent work has shown that listeners perceive segment boundaries at various levels of granularity. If centering models a universal processing phenomenon, it is implausible that each listener is using a different centering algorithm.The third issue is that even for utterances within a discourse segment, there are strong contrasts between utterances whose adjacent utterance within a segment is hierarchically recent and those whose adjacent utterance within a segment is linearly recent. This chapter argues that these problems can be eliminated by replacing Grosz and Sidner's stack model of attentional state with an alternate model, the cache model. I show how the cache model is easily integrated with the centering algorithm, and provide several types of data from naturally occurring discourses that support the proposed integrated model. Future work should provide additional support for these claims with an examination of a larger corpus of naturally occurring discourses.

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arXiv1997

Global Thresholding and Multiple Pass Parsing

We present a variation on classic beam thresholding techniques that is up to an order of magnitude faster than the traditional method, at the same performance level. We also present a new thresholding technique, global thresholding, which, combined with the new beam thresholding, gives an additional factor of two improvement, and a novel technique, multiple pass parsing, that can be combined with the others to yield yet another 50% improvement. We use a new search algorithm to simultaneously optimize the thresholding parameters of the various algorithms.

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arXiv1997

A complexity measure for diachronic Chinese phonology

This paper addresses the problem of deriving distance measures between parent and daughter languages with specific relevance to historical Chinese phonology. The diachronic relationship between the languages is modelled as a Probabilistic Finite State Automaton. The Minimum Message Length principle is then employed to find the complexity of this structure. The idea is that this measure is representative of the amount of dissimilarity between the two languages.

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arXiv1997

Fast Context-Free Parsing Requires Fast Boolean Matrix Multiplication

Valiant showed that Boolean matrix multiplication (BMM) can be used for CFG parsing. We prove a dual result: CFG parsers running in time $O(|G||w|^{3 - \myeps})$ on a grammar $G$ and a string $w$ can be used to multiply $m \times m$ Boolean matrices in time $O(m^{3 - \myeps/3})$. In the process we also provide a formal definition of parsing motivated by an informal notion due to Lang. Our result establishes one of the first limitations on general CFG parsing: a fast, practical CFG parser would yield a fast, practical BMM algorithm, which is not believed to exist.

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arXiv1997

DIA-MOLE: An Unsupervised Learning Approach to Adaptive Dialogue Models for Spoken Dialogue Systems

The DIAlogue MOdel Learning Environment supports an engineering-oriented approach towards dialogue modelling for a spoken-language interface. Major steps towards dialogue models is to know about the basic units that are used to construct a dialogue model and possible sequences. In difference to many other approaches a set of dialogue acts is not predefined by any theory or manually during the engineering process, but is learned from data that are available in an avised spoken dialogue system. The architecture is outlined and the approach is applied to the domain of appointment scheduling. Even though based on a word correctness of about 70% predictability of dialogue acts in DIA-MOLE turns out to be comparable to human-assigned dialogue acts.

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arXiv1997

Similarity-Based Methods For Word Sense Disambiguation

We compare four similarity-based estimation methods against back-off and maximum-likelihood estimation methods on a pseudo-word sense disambiguation task in which we controlled for both unigram and bigram frequency. The similarity-based methods perform up to 40% better on this particular task. We also conclude that events that occur only once in the training set have major impact on similarity-based estimates.

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arXiv1997

Encoding Frequency Information in Lexicalized Grammars

We address the issue of how to associate frequency information with lexicalized grammar formalisms, using Lexicalized Tree Adjoining Grammar as a representative framework. We consider systematically a number of alternative probabilistic frameworks, evaluating their adequacy from both a theoretical and empirical perspective using data from existing large treebanks. We also propose three orthogonal approaches for backing off probability estimates to cope with the large number of parameters involved.

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arXiv1997

Learning Methods for Combining Linguistic Indicators to Classify Verbs

Fourteen linguistically-motivated numerical indicators are evaluated for their ability to categorize verbs as either states or events. The values for each indicator are computed automatically across a corpus of text. To improve classification performance, machine learning techniques are employed to combine multiple indicators. Three machine learning methods are compared for this task: decision tree induction, a genetic algorithm, and log-linear regression.

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arXiv1997

Combining Multiple Methods for the Automatic Construction of Multilingual WordNets

This paper explores the automatic construction of a multilingual Lexical Knowledge Base from preexisting lexical resources. First, a set of automatic and complementary techniques for linking Spanish words collected from monolingual and bilingual MRDs to English WordNet synsets are described. Second, we show how resulting data provided by each method is then combined to produce a preliminary version of a Spanish WordNet with an accuracy over 85%. The application of these combinations results on an increment of the extracted connexions of a 40% without losing accuracy. Both coarse-grained (class level) and fine-grained (synset assignment level) confidence ratios are used and evaluated. Finally, the results for the whole process are presented.

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arXiv1997

Off-line Parsability and the Well-foundedness of Subsumption

Typed feature structures are used extensively for the specification of linguistic information in many formalisms. The subsumption relation orders TFSs by their information content. We prove that subsumption of acyclic TFSs is well-founded, whereas in the presence of cycles general TFS subsumption is not well-founded. We show an application of this result for parsing, where the well-foundedness of subsumption is used to guarantee termination for grammars that are off-line parsable. We define a new version of off-line parsability that is less strict than the existing one; thus termination is guaranteed for parsing with a larger set of grammars.

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arXiv1997

Using Single Layer Networks for Discrete, Sequential Data: An Example from Natural Language Processing

A natural language parser which has been successfully implemented is described. This is a hybrid system, in which neural networks operate within a rule based framework. It can be accessed via telnet for users to try on their own text. (For details, contact the author.) Tested on technical manuals, the parser finds the subject and head of the subject in over 90% of declarative sentences. The neural processing components belong to the class of Generalized Single Layer Networks (GSLN). In general, supervised, feed-forward networks need more than one layer to process data. However, in some cases data can be pre-processed with a non-linear transformation, and then presented in a linearly separable form for subsequent processing by a single layer net. Such networks offer advantages of functional transparency and operational speed. For our parser, the initial stage of processing maps linguistic data onto a higher order representation, which can then be analysed by a single layer network. This transformation is supported by information theoretic analysis.

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arXiv1997

Segmentation of Expository Texts by Hierarchical Agglomerative Clustering

We propose a method for segmentation of expository texts based on hierarchical agglomerative clustering. The method uses paragraphs as the basic segments for identifying hierarchical discourse structure in the text, applying lexical similarity between them as the proximity test. Linear segmentation can be induced from the identified structure through application of two simple rules. However the hierarchy can be used also for intelligent exploration of the text. The proposed segmentation algorithm is evaluated against an accepted linear segmentation method and shows comparable results.

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