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arXiv1994

Aligning a Parallel English-Chinese Corpus Statistically with Lexical Criteria

We describe our experience with automatic alignment of sentences in parallel English-Chinese texts. Our report concerns three related topics: (1) progress on the HKUST English-Chinese Parallel Bilingual Corpus; (2) experiments addressing the applicability of Gale & Church's length-based statistical method to the task of alignment involving a non-Indo-European language; and (3) an improved statistical method that also incorporates domain-specific lexical cues.

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arXiv1994

Parsing Turkish with the Lexical Functional Grammar Formalism

This paper describes our work on parsing Turkish using the lexical-functional grammar formalism. This work represents the first significant effort for parsing Turkish. Our implementation is based on Tomita's parser developed at Carnegie-Mellon University Center for Machine Translation. The grammar covers a substantial subset of Turkish including simple and complex sentences, and deals with a reasonable amount of word order freeness. The complex agglutinative morphology of Turkish lexical structures is handled using a separate two-level morphological analyzer. After a discussion of key relevant issues regarding Turkish grammar, we discuss aspects of our system and present results from our implementation. Our initial results suggest that our system can parse about 82\% of the sentences directly and almost all the remaining with very minor pre-editing.

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arXiv1994

An Automatic Method of Finding Topic Boundaries

This article outlines a new method of locating discourse boundaries based on lexical cohesion and a graphical technique called dotplotting. The application of dotplotting to discourse segmentation can be performed either manually, by examining a graph, or automatically, using an optimization algorithm. The results of two experiments involving automatically locating boundaries between a series of concatenated documents are presented. Areas of application and future directions for this work are also outlined.

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arXiv1994

TDL--- A Type Description Language for Constraint-Based Grammars

This paper presents \tdl, a typed feature-based representation language and inference system. Type definitions in \tdl\ consist of type and feature constraints over the boolean connectives. \tdl\ supports open- and closed-world reasoning over types and allows for partitions and incompatible types. Working with partially as well as with fully expanded types is possible. Efficient reasoning in \tdl\ is accomplished through specialized modules.

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arXiv1994

DPOCL: A Principled Approach to Discourse Planning

Research in discourse processing has identified two representational requirements for discourse planning systems. First, discourse plans must adequately represent the intentional structure of the utterances they produce in order to enable a computational discourse agent to respond effectively to communicative failures \cite{MooreParisCL}. Second, discourse plans must represent the informational structure of utterances. In addition to these representational requirements, we argue that discourse planners should be formally characterizable in terms of soundness and completeness.

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arXiv1994

A Spanish Tagset for the CRATER Project

This working paper describes the Spanish tagset to be used in the context of CRATER, a CEC funded project aiming at the creation of a multilingual (English, French, Spanish) aligned corpus using the International Telecommunications Union corpus. In this respect, each version of the corpus will be (or is currently) tagged. Xerox PARC tagger will be adapted to Spanish in order to perform the tagging of the Spanish version. This tagset has been devised as the ideal one for Spanish, and has been posted to several lists in order to get feedback to it.

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arXiv1994

Analyzing and Improving Statistical Language Models for Speech Recognition

In many current speech recognizers, a statistical language model is used to indicate how likely it is that a certain word will be spoken next, given the words recognized so far. How can statistical language models be improved so that more complex speech recognition tasks can be tackled? Since the knowledge of the weaknesses of any theory often makes improving the theory easier, the central idea of this thesis is to analyze the weaknesses of existing statistical language models in order to subsequently improve them. To that end, we formally define a weakness of a statistical language model in terms of the logarithm of the total probability, LTP, a term closely related to the standard perplexity measure used to evaluate statistical language models. We apply our definition of a weakness to a frequently used statistical language model, called a bi-pos model. This results, for example, in a new modeling of unknown words which improves the performance of the model by 14% to 21%. Moreover, one of the identified weaknesses has prompted the development of our generalized N-pos language model, which is also outlined in this thesis. It can incorporate linguistic knowledge even if it extends over many words and this is not feasible in a traditional N-pos model. This leads to a discussion of whatknowledge should be added to statistical language models in general and we give criteria for selecting potentially useful knowledge. These results show the usefulness of both our definition of a weakness and of performing an analysis of weaknesses of statistical language models in general.

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arXiv1994

A Computational Model of Syntactic Processing: Ambiguity Resolution from Interpretation

Syntactic ambiguity abounds in natural language, yet humans have no difficulty coping with it. In fact, the process of ambiguity resolution is almost always unconscious. But it is not infallible, however, as example 1 demonstrates. 1. The horse raced past the barn fell. This sentence is perfectly grammatical, as is evident when it appears in the following context: 2. Two horses were being shown off to a prospective buyer. One was raced past a meadow. and the other was raced past a barn. ... Grammatical yet unprocessable sentences such as 1 are called `garden-path sentences.' Their existence provides an opportunity to investigate the human sentence processing mechanism by studying how and when it fails. The aim of this thesis is to construct a computational model of language understanding which can predict processing difficulty. The data to be modeled are known examples of garden path and non-garden path sentences, and other results from psycholinguistics. It is widely believed that there are two distinct loci of computation in sentence processing: syntactic parsing and semantic interpretation. One longstanding controversy is which of these two modules bears responsibility for the immediate resolution of ambiguity. My claim is that it is the latter, and that the syntactic processing module is a very simple device which blindly and faithfully constructs all possible analyses for the sentence up to the current point of processing. The interpretive module serves as a filter, occasionally discarding certain of these analyses which it deems less appropriate for the ongoing discourse than their competitors. This document is divided into three parts. The first is introductory, and reviews a selection of proposals from the sentence processing literature. The second part explores a body of data which has been adduced in support of a theory of structural preferences --- one that is inconsistent with the present claim. I show how the current proposal can be specified to account for the available data, and moreover to predict where structural preference theories will go wrong. The third part is a theoretical investigation of how well the proposed architecture can be realized using current conceptions of linguistic competence. In it, I present a parsing algorithm and a meaning-based ambiguity resolution method.

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arXiv1994

A Psycholinguistically Motivated Parser for CCG

Considering the speed in which humans resolve syntactic ambiguity, and the overwhelming evidence that syntactic ambiguity is resolved through selection of the analysis whose interpretation is the most `sensible', one comes to the conclusion that interpretation, hence parsing take place incrementally, just about every word. Considerations of parsimony in the theory of the syntactic processor lead one to explore the simplest of parsers: one which represents only analyses as defined by the grammar and no other information. Toward this aim of a simple, incremental parser I explore the proposal that the competence grammar is a Combinatory Categorial Grammar (CCG). I address the problem of the proliferating analyses that stem from CCG's associativity of derivation. My solution involves maintaining only the maximally incremental analysis and, when necessary, computing the maximally right-branching analysis. I use results from the study of rewrite systems to show that this computation is efficient.

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arXiv1994

Anytime Algorithms for Speech Parsing?

This paper discusses to which extent the concept of ``anytime algorithms'' can be applied to parsing algorithms with feature unification. We first try to give a more precise definition of what an anytime algorithm is. We arque that parsing algorithms have to be classified as contract algorithms as opposed to (truly) interruptible algorithms. With the restriction that the transaction being active at the time an interrupt is issued has to be completed before the interrupt can be executed, it is possible to provide a parser with limited anytime behavior, which is in fact being realized in our research prototype.

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arXiv1994

Decision Lists for Lexical Ambiguity Resolution: Application to Accent Restoration in Spanish and French

This paper presents a statistical decision procedure for lexical ambiguity resolution. The algorithm exploits both local syntactic patterns and more distant collocational evidence, generating an efficient, effective, and highly perspicuous recipe for resolving a given ambiguity. By identifying and utilizing only the single best disambiguating evidence in a target context, the algorithm avoids the problematic complex modeling of statistical dependencies. Although directly applicable to a wide class of ambiguities, the algorithm is described and evaluated in a realistic case study, the problem of restoring missing accents in Spanish and French text.

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arXiv1994

Multi-Paragraph Segmentation of Expository Text

This paper describes TextTiling, an algorithm for partitioning expository texts into coherent multi-paragraph discourse units which reflect the subtopic structure of the texts. The algorithm uses domain-independent lexical frequency and distribution information to recognize the interactions of multiple simultaneous themes. Two fully-implemented versions of the algorithm are described and shown to produce segmentation that corresponds well to human judgments of the major subtopic boundaries of thirteen lengthy texts.

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arXiv1994

Japanese word sense disambiguation based on examples of synonyms

(This is not the abstract): The language is Japanese. If your printer does not have fonts for Japases characters, the characters in figures will not be printed out correctly. Dissertation for Bachelor's degree at Kyoto University(Nagao lab.),March 1994.

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arXiv1994

Specifying Intonation from Context for Speech Synthesis

This paper presents a theory and a computational implementation for generating prosodically appropriate synthetic speech in response to database queries. Proper distinctions of contrast and emphasis are expressed in an intonation contour that is synthesized by rule under the control of a grammar, a discourse model, and a knowledge base. The theory is based on Combinatory Categorial Grammar, a formalism which easily integrates the notions of syntactic constituency, semantics, prosodic phrasing and information structure. Results from our current implementation demonstrate the system's ability to generate a variety of intonational possibilities for a given sentence depending on the discourse context.

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arXiv1994

Generating Context-Appropriate Word Orders in Turkish

Turkish has considerably freer word order than English. The interpretations of different word orders in Turkish rely on information that describes how a sentence relates to its discourse context. To capture the syntactic features of a free word order language, I present an adaptation of Combinatory Categorial Grammars called {}-CCGs (set-CCGs). In {}-CCGs, a verb's subcategorization requirements are relaxed so that it requires a set of arguments without specifying their linear order. I integrate a level of information structure, representing pragmatic functions such as topic and focus, with {}-CCGs to allow certain pragmatic distinctions in meaning to influence the word order of a sentence in a compositional way. Finally, I discuss how this strategy is used within an implemented generation system which produces Turkish sentences with context-appropriate word orders in a simple database query task.

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arXiv1994

Generating Multilingual Documents from a Knowledge Base: The TECHDOC Project

TECHDOC is an implemented system demonstrating the feasibility of generating multilingual technical documents on the basis of a language-independent knowledge base. Its application domain is user and maintenance instructions, which are produced from underlying plan structures representing the activities, the participating objects with their properties, relations, and so on. This paper gives a brief outline of the system architecture and discusses some recent developments in the project: the addition of actual event simulation in the KB, steps towards a document authoring tool, and a multimodal user interface. (slightly corrected version of a paper to appear in: COLING 94, Proceedings)

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arXiv1994

Tracking Point of View in Narrative

Third-person fictional narrative text is composed not only of passages that objectively narrate events, but also of passages that present characters' thoughts, perceptions, and inner states. Such passages take a character's ``psychological point of view''. A language understander must determine the current psychological point of view in order to distinguish the beliefs of the characters from the facts of the story, to correctly attribute beliefs and other attitudes to their sources, and to understand the discourse relations among sentences. Tracking the psychological point of view is not a trivial problem, because many sentences are not explicitly marked for point of view, and whether the point of view of a sentence is objective or that of a character (and if the latter, which character it is) often depends on the context in which the sentence appears. Tracking the psychological point of view is the problem addressed in this work. The approach is to seek, by extensive examinations of naturally-occurring narrative, regularities in the ways that authors manipulate point of view, and to develop an algorithm that tracks point of view on the basis of the regularities found. This paper presents this algorithm, gives demonstrations of an implemented system, and describes the results of some preliminary empirical studies, which lend support to the algorithm.

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