1. Articles in category: Parsing

    73-96 of 563 « 1 2 3 4 5 6 7 ... 22 23 24 »
    1. Parsing of Myanmar sentences with function tagging. (arXiv:1205.1603v1 [cs.CL])

      This paper describes the use of Naive Bayes to address the task of assigning function tags and context free grammar (CFG) to parse Myanmar sentences. Part of the challenge of statistical function tagging for Myanmar sentences comes from the fact that Myanmar has free-phrase-order and a complex morphological system. Function tagging is a pre-processing step for parsing. In the task of function tagging, we use the functional annotated corpus and tag Myanmar sentences with correct segmentation, POS (part-of-speech) tagging and chunking information. We propose Myanmar grammar rules and apply context free grammar (CFG) to find out the parse tree of ...
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      Mentions: Myanmar Bayes
    2. Geocoding multi-feature addresses

      A system and method of parsing natural language descriptions of features to determine an approximate location. An embodiment includes splitting the natural language descriptions into components, geocoding each component, and returning the geocode with the highest confidence level. The geocode references a specific location, and this information may be determined by content from a variety of sources. The system may use an assortment of techniques for determining highest confidence level.
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    3. A new approach for recognizing handwritten mathematics using relational grammars and fuzzy sets

      Abstract  We present a new approach for parsing two-dimensional input using relational grammars and fuzzy sets. A fast, incremental parsing algorithm is developed, motivated by the two-dimensional structure of written mathematics. The approach reports all identifiable parses of the input. The parses are represented as a fuzzy set, in which the membership grade of a parse measures the similarity between it and the handwritten input. To identify and report parses efficiently, we adapt and apply existing techniques such as rectangular partitions and shared parse forests, and introduce new ideas such as relational classes and interchangeability. We also present a correction ...
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    4. A Computational Grammar of Sinhala

      A Computational Grammar for a language is a very useful resource for carrying out various language processing tasks for that language such as Grammar checking, Machine Translation and Question Answering. As is the case in most South Indian Languages, Sinhala is a highly inflected language with three gender forms and two number forms among other grammatical features. While piecemeal descriptions of Sinhala grammar is reported in the literature, no comprehensive effort to develop a context-free grammar (CFG) has been made that has been able to account for any significant coverage of the language. This paper describes the development of a ...
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      Mentions: Colombo Nltk
    5. Can Modern Statistical Parsers Lead to Better Natural Language Understanding for Education?

      We use state-of-the-art parsing technology to build GeoSynth – a system that can automatically solve word problems in geometric constructions. Through our experiments we show that even though off-the-shelf parsers perform poorly on texts containing specialized vocabulary and long sentences, appropriate preprocessing of text before applying the parser and use of extensive domain knowledge while interpreting the parse tree can together help us circumvent parser errors and build robust domain specific natural language understanding modules useful for various educational applications. Content Type Book ChapterPages 415-427DOI 10.1007/978-3-642-28604-9_34Authors Umair Z. Ahmed, Microsoft Research India, “Vigyan”, #9, Lavelle Road, Bangalore, 560 025 ...
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    6. Coreference Resolution Using Tree CRFs

      Coreference resolution is the task of identifying which noun phrases or mentions refer to the same real-world entity in a text or a dialogue. This is an essential task in many of the NLP applications such as information extraction, question answering system, summarization, machine translation and in information retrieval systems. Coreference Resolution is traditionally considered as pairwise classification problem and different classification techniques are used to make a local classification decision. We are using Tree-CRF for this task. With Tree-CRF we make a joint prediction of the anaphor and the antecedent. Tree-based Reparameterization (TRP) for approximate inference is used for ...
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    7. Semiring Parsing

      Syntactic parsing is an important task in natural language processing (NLP). In this chapter an application of semiring theory in parsing (a.k.a.”semiring parsing”) will be introduced. A semiring parsing framework is proposed and studied in [6]. Content Type Book ChapterPages 175-192DOI 10.1007/978-3-642-27641-5_10Authors Yudong Liu, Computer Science Department, Western Washington University, Bellinig ham, Washington, USA Book Series Studies in Fuzziness and Soft ComputingOnline ISSN 1860-0808Print ISSN 1434-9922 Book Series Volume Volume 278/2012 Book Fuzzy Semirings with Applications to Automata TheoryDOI 10.1007/978-3-642-27641-5Print ISBN 978-3-642-27640-8
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      Mentions: Washington
    8. The Horse Raced Past: Gardenpath Processing in Dynamical Systems. (arXiv:1203.0145v1 [cs.CL])

      I pinpoint an interesting similarity between a recent account to rational parsing and the treatment of sequential decisions problems in a dynamical systems approach. I argue that expectation-driven search heuristics aiming at fast computation resembles a high-risk decision strategy in favor of large transition velocities. Hale's rational parser, combining generalized left-corner parsing with informed $\mathrm{A}^*$ search to resolve processing conflicts, explains gardenpath effects in natural sentence processing by misleading estimates of future processing costs that are to be minimized. On the other hand, minimizing the duration of cognitive computations in time-continuous dynamical systems can be described by combining ...
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    9. Recognition of tabular structures

      A number of regions and partitions may be created based on input handwritten atoms and a grammar parsing framework. Productions for tabular structures may be added to the grammar parsing framework to produce an extended grammar parsing framework. Each of the regions may be searched for a tabular structure. Upon finding a tabular structure, a type of tabular structure may be determined. Configuration partitions may be created, based on the added productions, and added to the created partitions. A set of configuration regions may be created based on the configuration partitions and added to the created regions. The productions for ...
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    10. Recognizing Bangla Grammar using Predictive Parser. (arXiv:1201.2010v1 [cs.CL])

      We describe a Context Free Grammar (CFG) for Bangla language and hence we propose a Bangla parser based on the grammar. Our approach is very much general to apply in Bangla Sentences and the method is well accepted for parsing a language of a grammar. The proposed parser is a predictive parser and we construct the parse table for recognizing Bangla grammar. Using the parse table we recognize syntactical mistakes of Bangla sentences when there is no entry for a terminal in the parse table. If a natural language can be successfully parsed then grammar checking from this language becomes ...
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      Mentions: Bangla
    11. Grammatical Relations of Myanmar Sentences Augmented by Transformation-Based Learning of Function Tagging. (arXiv:1112.0396v1 [cs.CL])

      In this paper we describe function tagging using Transformation Based Learning (TBL) for Myanmar that is a method of extensions to the previous statistics-based function tagger. Contextual and lexical rules (developed using TBL) were critical in achieving good results. First, we describe a method for expressing lexical relations in function tagging that statistical function tagging are currently unable to express. Function tagging is the preprocessing step to show grammatical relations of the sentences. Then we use the context free grammar technique to clarify the grammatical relations in Myanmar sentences or to output the parse trees. The grammatical relations are the ...
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      Mentions: Myanmar TBL
    12. Chinese Zero Anaphor Detection: Rule-Based Approach

      A rule-based approach for Chinese zero anaphor detection is proposed. Given a parse tree, the smallest IP sub-tree covering the current predicate is captured. Based on this IP sub-tree, some rules are proposed for detecting whether a Chinese zero anaphor exists. This paper also systematically evaluates the rule-based method on OntoNotes corpus. Using golden parse tree, our method achieves 82.45 in F-measure. And the F-measure is 63.84 using automatic parser. The experiment results show that our method is very effective on Chinese zero anaphor detection. Content Type Book ChapterPages 403-407DOI 10.1007/978-3-642-25661-5_52Authors Kaiwei Qin, School of Computer ...
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    13. Modular Natural Language Processing Using Declarative Attribute Grammars

      A system based on a general top-down parsing algorithm has been developed which allows language processors to be created as executable specifications of arbitrary attribute grammars. Declarative notation of attribute grammars allows modular construction of executable language definitions. Syntax is defined through general context-free grammar rules, and meaning is defined by associated semantic rules with arbitrary dependencies. An innovative technique allows parses to be pruned by arbitrary semantic constraints. This new technique is useful in modelling natural-language phenomena by imposing unification-like restrictions, and accommodating long-distance and cross-serial dependencies, which cannot be handled by context-free rules alone. Content Type Book ChapterPages ...
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      Mentions: Canada
    14. Simple, Functional, Sound and Complete Parsing for All Context-Free Grammars

      Parsers for context-free grammars can be implemented directly and naturally in a functional style known as “combinator parsing”, using recursion following the structure of the grammar rules. However, naive implementations fail to terminate on left-recursive grammars, and despite extensive research the only complete parsers for general context-free grammars are constructed using other techniques such as Earley parsing. Our main contribution is to show how to construct simple, sound and complete parser implementations directly from grammar specifications, for all context-free grammars, based on combinator parsing. We then construct a generic parser generator and show that generated parsers are sound and complete ...
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    15. Discriminative Latent Variable Grammars

      As we saw in the previous chapter, learning a refined latent variable grammar involves the estimation of a set of grammar parameters θ on latent annotations despite the fact that the original trees lack the latent annotations. In the previous chapter, we considered generative grammars, where the parameters θ are set to maximize the joint likelihood of the training sentences and their parse trees. In this section we will consider discriminative grammars, where the parameters θ are set to maximize the likelihood of the correct parse tree (vs. all possible trees) given a sentence. Content Type Book ChapterPages 47-67DOI 10 ...
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      Mentions: New York Google
    16. Latent Variable Grammars for Natural Language Parsing

      As described in Chap. 1, parsing is the process of analyzing the syntactic structure of natural language sentences and will be fundamental for building systems that can understand natural languages. Probabilistic context-free grammars (PCFGs) underlie most high-performance parsers in one way or another (Charniak 2000; Collins 1999; Charniak and Johnson 2005; Huang 2008). However, as demonstrated by Charniak (1996) and Klein and Manning (2003a), a PCFG which simply takes the empirical rules and probabilities off of a treebank does not perform well. This naive grammar is a poor one because its context-freedom assumptions are too strong in some places (e ...
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    17. Efficient accurate syntactic direct translation models: one tree at a time

      Abstract  A challenging aspect of Statistical Machine Translation from Arabic to English lies in bringing the Arabic source morpho-syntax to bear on the lexical as well as word-order choices of the English target string. In this article, we extend the feature-rich discriminative Direct Translation Model 2 (DTM2) with a novel linear-time parsing algorithm based on an eager, incremental interpretation of Combinatory Categorial Grammar. This way we can reap the benefits of a target syntactic enhancement that leads to more grammatical output while also enabling dynamic decoding without the risk of blowing up decoding space and time requirements. Our model defines ...
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    18. Processing Text-Technological Resources in Discourse Parsing

      Discourse parsing of complex text types such as scientific research articles requires the analysis of an input document on linguistic and structural levels that go beyond traditionally employed lexical discourse markers. This chapter describes a text-technological approach to discourse parsing. Discourse parsing with the aim of providing a discourse structure is seen as the addition of a new annotation layer for input documents marked up on several linguistic annotation levels. The discourse parser generates discourse structures according to the Rhetorical Structure Theory. An overview of the knowledge sources and components for parsing scientific journal articles is given. The parser’s ...
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    19. Fence - An Efficient Parser with Ambiguity Support for Model-Driven Language Specification. (arXiv:1107.4687v2 [cs.CL] UPDATED)

      Model-based language specification has applications in the implementation of language processors, the design of domain-specific languages, model-driven software development, data integration, text mining, natural language processing, and corpus-based induction of models. Model-based language specification decouples language design from language processing and, unlike traditional grammar-driven approaches, which constrain language designers to specific kinds of grammars, it needs general parser generators able to deal with ambiguities. In this paper, we propose Fence, an efficient bottom-up parsing algorithm with lexical and syntactic ambiguity support that enables the use of model-based language specification in practice.
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    20. A Constraint-Satisfaction Parser for Context-Free Grammars. (arXiv:1110.1470v1 [cs.CL])

      Traditional language processing tools constrain language designers to specific kinds of grammars. In contrast, model-based language specification decouples language design from language processing. As a consequence, model-based language specification tools need general parsers able to parse unrestricted context-free grammars. As languages specified following this approach may be ambiguous, parsers must deal with ambiguities. Model-based language specification also allows the definition of associativity, precedence, and custom constraints. Therefore parsers generated by model-driven language specification tools need to enforce constraints. In this paper, we propose Fence, an efficient bottom-up chart parser with lexical and syntactic ambiguity support that allows the specification of ...
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    21. The Generative Power of Probabilistic and Weighted Context-Free Grammars

      Over the last decade, probabilistic parsing has become the standard in the parsing literature where one of the purposes of those probabilities is to discard unlikely parses. We investigate the effect that discarding low probability parses has on both the weak and strong generative power of context-free grammars. We prove that probabilistic context-free grammars are more powerful than their non-probabilistic counterparts but in a way that is orthogonal to the Chomsky hierarchy. In particular, we show that the increase in power cannot be used to model any dependencies that discrete context-free grammars cannot. Content Type Book ChapterPages 57-71DOI 10.1007 ...
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    22. Multi-task Learning for Word Alignment and Dependency Parsing

      Word alignment and parsing are two important components for syntax based machine translation. The inconsistent models for alignment and parsing caused problems during translation pair extraction. In this paper, we do word alignment and dependency parsing in a multi-task learning framework, in which word alignment and dependency parsing are consistent and assisted with each other. Our experiments show significant improvement not only for both word alignment and dependency parsing, but also the final translation performance. Content Type Book ChapterPages 151-158DOI 10.1007/978-3-642-23896-3_18Authors Shujie Liu, Harbin Institute of Technology, No. 92, West Da-Zhi Street, Nangang District, Harbin City, China Book ...
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    23. Method and apparatus for training a prosody statistic model and prosody parsing, method and system for text to speech synthesis

      TECHNICAL FIELD OF THE INVENTION The present invention relates to the technology of voice synthesis, in particular, to the technology of prosody parsing in voice synthesis and the technology of training a prosody statistic model.BACKGROUND OF THE INVENTION The goal of a system for text to speech synthesis (TTS) is to make a computer speak out natural voice as a man does. When a man is reading a sentence naturally, apart from some of the punctuations (e.g. period, comma, etc.) as inherent pausein
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      Mentions: San Mateo A. Waibel
    73-96 of 563 « 1 2 3 4 5 6 7 ... 22 23 24 »
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