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d1785607
The ultimate goal when building dialogue systems is to satisfy the needs of real users, but quality assurance for dialogue strategies is a non-trivial problem. The applied evaluation metrics and resulting design principles are often obscure, emerge by trial-and-error, and are highly context dependent. This paper introd...
Automatic Learning and Evaluation of User-Centered Objective Functions for Dialogue System Optimisation
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The paper proposes a methodology for dealing with multiword expressions in natural language processing applications. It provides a practically justified taxonomy of such units, and suggests the ways in which the individual classes can be processed computationally. While the study is currently limited to Polish and Engl...
A Practical Classification of Multiword Expressions
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Uyghur is one of the Turkic languages in the Altaic language family. We are developing a machine translation system to translate from English into Uyghur. As there are no previous researches devoted to machine translation between English and Uyghur and being short of related works that we could use as a base for our re...
Comparative Study on Japanese and Uyghur Grammars for An English- Uyghur Machine Translation System
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We address the problem of translating from morphologically poor to morphologically rich languages by adding per-word linguistic information to the source language. We use the syntax of the source sentence to extract information for noun cases and verb persons and annotate the corresponding words accordingly. In experim...
Enriching Morphologically Poor Languages for Statistical Machine Translation
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In this paper, we explore ways of improving an inference rule collection and its application to the task of recognizing textual entailment. For this purpose, we start with an automatically acquired collection and we propose methods to refine it and obtain more rules using a hand-crafted lexical resource. Following this...
Inference Rules and their Application to Recognizing Textual Entailment
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Discriminative training methods are used in statistical machine translation to effectively introduce and combine additional knowledge sources within the translation process. Although these methods are described in the accompanying literature and comparative studies are available for speech recognition, additional consi...
Considerations in Maximum Mutual Information and Minimum Classification Error training for Statistical Machine Translation
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We propose methods for estimating the probability that an entity from an entity database is associated with a web search query. Association is modeled using a query entity click graph, blending general query click logs with vertical query click logs. Smoothing techniques are proposed to address the inherent data sparsi...
Jigs and Lures: Associating Web Queries with Structured Entities
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This paper presents the results of using Roget's International Thesaurus as the taxonomy in a semantic similarity measurement task. Four similarity metrics were taken from the literature and applied to Roget's. The experimental evaluation suggests that the traditional edge counting approach does surprisingly well (a co...
A Comparison of WordNet and Roget's Taxonomy for Measuring Semantic Similarity
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Using a novel approach, we examine which cues in a fingerspelling stream, namely holds or transitions, allow for more successful comprehension by students learning American Sign Language (ASL). Sixteen university-level ASL students participated in this study. They were shown video clips of a native signer fingerspellin...
Exploring factors that contribute to successful fingerspelling comprehension
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SentimentWortschatz, or SentiWS for short, is a publicly available German-language resource for sentiment analysis, opinion mining etc. It lists positive and negative sentiment bearing words weighted within the interval of [−1; 1] plus their part of speech tag, and if applicable, their inflections. The current version ...
SentiWS -a Publicly Available German-language Resource for Sentiment Analysis
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In the last few years, so called finite.state morphology, in general, and two-level morphology in particular, have become widely accepted as paradigms for the computational treatment of morphology.Finite-state morphology appeals to the notion of a finite-state transducer, which is simply a classical finite-state automa...
Nonconcatenative Finite-State Morphology
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This paper presents pilot work integrating machine labeling and active learning with human annotation of data for the language documentation task of creating interlinearized gloss text (IGT) for the Mayan language Uspanteko. The practical goal is to produce a totally annotated corpus that is as accurate as possible giv...
Evaluating Automation Strategies in Language Documentation
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We introduce automatic verification as a post-processing step for entity linking (EL). The proposed method trusts EL system results collectively, by assuming entity mentions are mostly linked correctly, in order to create a semantic profile of the given text using geospatial and temporal information, as well as fine-gr...
Trust, but Verify! Better Entity Linking through Automatic Verification Chin-Yew Lin Microsoft Research
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In (Chen, 2009), we show that for a variety of language models belonging to the exponential family, the test set cross-entropy of a model can be accurately predicted from its training set cross-entropy and its parameter values. In this work, we show how this relationship can be used to motivate two heuristics for "shri...
Shrinking Exponential Language Models
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We present Jane, RWTH's hierarchical phrase-based translation system, which has been open sourced for the scientific community. This system has been in development at RWTH for the last two years and has been successfully applied in different machine translation evaluations. It includes extensions to the hierarchical ap...
Jane: Open Source Hierarchical Translation, Extended with Reordering and Lexicon Models
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This paper analyzes the results of automatic concept alignment between two ontologies. We use an iterative algorithm to perform concept alignment. The algorithm uses the similarity of shared terms in order to find the most appropriate target concept for a particular source concept. The results show that the proposed al...
Analysis of an Iterative Algorithm for Term-Based Ontology Alignment
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Speech prosody is known to be central in advanced communication technologies. However, despite the advances of theoretical studies in speech prosody, so far, no large scale prosody annotated resources that would facilitate empirical research and the development of empirical computational approaches are available. This ...
An Automatic Prosody Tagger for Spontaneous Speech
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This paper describes Eksairesis, a system for learning economic domain knowledge automatically from Modern Greek text. The knowledge is in the form of economic terms and the semantic relations that govern them. The entire process in based on the use of minimal language-dependent tools, no external linguistic resources,...
Eksairesis: A Domain-adaptable System for Ontology Building from Unstructured Text
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In this paper, we propose a lexical selection method with three steps: sense disambiguation of source words, sense-to-word mapping, and selection of the most appropriate target language lexical item. The knowledge for each step is extracted from a machine readable dictionary and a target language monolingual corpus. By...
Lexical Selection with a Target Language Monolingual Corpus and an MRD
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SemEval-2 Task 15: Infrequent Sense Identification for Mandarin Text to Speech Systems
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The CoNLL-SIGMORPHON 2018 shared task on supervised learning of morphological generation featured data sets from 103 typologically diverse languages. Apart from extending the number of languages involved in earlier supervised tasks of generating inflected forms, this year the shared task also featured a new second task...
The CoNLL-SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection
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A part-of-speech tagged corpus is a very hnportant knowledge source for natural language processing researchers. 'Poday, several part-of-speech tagged corpora are readily available for research use. [Iowever, because there is wide diversity of morphological information systems (word-segmentation~ part-of-speech system,...
Restructuring Tagged Corpora with Morpheme Adjustment Rules
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Usually, human-computer dialogue systems rely on ad-hoc solutions for the component performing speech turn generation, in natural language. However, integration of taskspecific and general world knowledge in order to provide a more reliable and natural interaction with humans also through more sophisticated language ge...
Using Speech Acts in Logic-Based Rhetorical Structuring for Natural Language Generation in Human-Computer Dialogue
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In this study, we propose and implement a concatenation-based audio signal synthesis system for the engine noises of continuously varying speed. A user simply draws the engine speed curve through an interface, and the corresponding audio signal is synthesized as output. This drawable interface makes the input function ...
Concatenation-based Method for the Synthesis of Engine Noise with Continuously Varying Speed
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ADAPTIVE DIALOGUE -THE BASIS FOR PERSONAL COMPUTER SYSTEM
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Motif analysis counts the number of small building blocks (the motifs) in a network and relates these statistical numbers to the inherent semantics of the network. In the realm of natural language processing, the networks are induced by texts. We demonstrate that motif analysis may help assess the quality of a document...
Network Motifs May Improve Quality Assessment of Text Documents
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Procedural dialog systems can help users achieve a wide range of goals. However, such systems are challenging to build, currently requiring manual engineering of substantial domain-specific task knowledge and dialog management strategies. In this paper, we demonstrate that it is possible to learn procedural dialog syst...
Lightly Supervised Learning of Procedural Dialog Systems
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Current word alignment models for statistical machine translation do not address morphology beyond merely splitting words. We present a two-level alignment model that distinguishes between words and morphemes, in which we embed an IBM Model 1 inside an HMM based word alignment model. The model jointly induces word and ...
Simultaneous Word-Morpheme Alignment for Statistical Machine Translation
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In this article we investigate the translation of financial terms from English into German in the isolation of an ontology vocabulary. For this study we automatically built new domain-specific resources from the translation search engine Linguee and from the online encyclopaedia Wikipedia. Due to the fact that we perfo...
Experiments with Term Translation
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The paper discusses HPSG as a framework for the computational analysis of Mandarin Chinese. We point out the main characteristics of the framework and show how they can be exploited to target languagespecific issues, describe existing grammar engineering work for Chinese and present our own effort in the implementation...
Valence alternations and marking structures in a HPSG grammar for Mandarin Chinese
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The paper presents the embedding of an original parsing strategy for Romanian,called Segmentation-Cohesion-Dependency (SCD) , into Chomsk~'s well-known Government and Binding (BG) theory. In order to bring closer the SCD concepts and techniques to the GB theory, the following questions have had to be dealt with: (1) a ...
AUGMENTED X' -SCHEMES
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We report about the current state of development of a document suite and its applications. This collection of tools for the flexible and robust processing of documents in German is based on the use of XML as unifying formalism for encoding input and output data as well as process information. It is organized in modules...
An XML-based document suite
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We developed a time-domain normalization procedure which uses a speech signal and its corresponding speech rate contour as an input, and produces the normalized speech signal. Then we normalized the speech rate of a large spoken language resource of German read speech. We compared the resulting segment durations with t...
Reducing Segmental Duration Variation by Local Speech Rate Normalization of Large Spoken Language Resources
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The VESPRA system is designed for the processing of chains of (not connected utterances of) wordforms. These strings of wordforms correspond to sentences
A DESCRIPTION OF THE VESPRA SPEECH PROCESSING SYSTEM
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We present a corpus-based supervised learning system for coarse-grained sense disambiguation. In addition to usual features for training in word sense disambiguation, our system also uses Base Level Concepts automatically obtained from WordNet. Base Level Concepts are some synsets that generalize a hyponymy sub-hierarc...
GPLSI: Word Coarse-grained Disambiguation aided by Basic Level Concepts *
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Semantic knowledge has been adopted recently for SMT preprocessing, decoding and evaluation, in order to be able to compare sentences based on their meaning rather than on mere lexical and syntactic similarity. Little attention has been paid to semantic knowledge in the context of integrating fuzzy matches from a trans...
Semantics-based pretranslation for SMT using fuzzy matches
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Chinese word segmentation systems necessarily perform both accurately and quickly for real applications. In this paper, we study on word boundary decision (WBD) approach for Chinese word segmentation and implement it as a 2-tag character tagging with conditional random filed (CRF). With a help of tag transition feature...
Word Boundary Decision with CRF for Chinese Word Segmentation * * * *
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Speech recognition systems incorporate a language model which, at each stage of the recognition task, assigns a probability of occurrence to each word in the vocabulary. A class of Markov langnage models identified by Jclinek has achieved consider-. able success in this domain. A modification of the Markov approach, wb...
SPEECH RECOGNITION AND THE FREQUENCY OF RECENTLY USED WORDS A MODIFIED MARKOV MODEL FOR NATURAL LANGUAGE
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In this talk I will describe two attempts at introducing syntactic structure into semantic models using neural network architectures. The first study focuses on a particular grammatical construction, namely relative clauses, and centers around the design of a new dataset for testing compositional distributional models....
Introducing Structure into Neural Network-Based Semantic Models
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The freely available SPaRKy sentence planner uses hand-written weighted rules for sentence plan construction, and a useror domain-specific second-stage ranker for sentence plan selection. However, coming up with sentence plan construction rules for a new domain can be difficult. In this paper, we automatically extract ...
Evaluating automatic extraction of rules for sentence plan construction
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Due to the increase in the number and depth of analyses required over the text, like entity recognition, POS tagging, syntactic analysis, etc. the annotation in-line has become unpractical. In Natural Language Processing (NLP) some emphasis has been placed in finding an annotation method to solve this problem. A possib...
Iula2Standoff: a tool for creating standoff documents for the IULACT
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When reporting the news, journalists rely on the statements of stakeholders, experts, and officials. The attribution of such a statement is verifiable if its fidelity to the source can be confirmed or denied. In this paper, we develop a new NLP task: determining the verifiability of an attribution based on linguistic c...
Assessing the Verifiability of Attributions in News Text
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Valence shifting is the task of rewriting a text towards more/less positively or negatively slanted versions. This paper presents a rule-based approach to producing Turkish sentences with varying sentiment. The approach utilizes semantic relations in the Turkish and English WordNets to determine word polarities and inv...
Generating Valence Shifted Turkish Sentences
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Learning to detect entity mentions without using syntactic information can be useful for integration and joint optimization with other tasks. However, it is common to have partially annotated data for this problem. Here, we investigate two approaches to deal with partial annotation of mentions: weighted loss and soft-t...
Partially-supervised Mention Detection
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An analysis that defines predicates for Wordnet verb classes and links them to semantic interpretation is presented. The selectional restrictions for the thematic roles defining the predicates are WordNet ontological categories. Thematic roles are also linked to the syntactic relations that realize them. The paper illu...
Linking WordNet Verb Classes to Semantic Interpretation
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This paper presents the process of development and the characteristics of an evaluation collection for a personalisation system for digital newspapers. This system selects, adapts and presents contents according to a user model that define information needs. The collection presented here contains data that are cross-re...
Development and Use of an Evaluation Collection for Personalisation of Digital Newspapers
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Automatically constructing knowledge bases from online resources has become a crucial task in many research areas. Most existing knowledge bases are built from English resources, while few efforts have been made for other languages. Building knowledge bases for Chinese is of great importance on its own right. However, ...
Towards Automatic Construction of Knowledge Bases from Chinese Online Resources
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This paper presents an empirical work for Vietnamese NP chunking task. We show how to build an annotation corpus of NP chunking and how discriminative sequence models are trained using the corpus. Experiment results using 5 fold cross validation test show that discriminative sequence learning are well suitable for Viet...
An Empirical Study of Vietnamese Noun Phrase Chunking with Discriminative Sequence Models
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Twitter has become one of the most import channels to spread latest scholarly information because of its fast information spread speed. How to predict whether a scholarly tweet will be retweeted is a key task in understanding the message propagation within large user communities. Hence, we present the real-time scholar...
Real-time Scholarly Retweeting Prediction System
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Automatically generating a natural language description of an image is a fundamental problem in artificial intelligence. This task involves both computer vision and natural language processing and is called "image caption generation." Research on image caption generation has typically focused on taking in an image and ...
Cross-Lingual Image Caption Generation
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This paper presents a method for designing, compiling and annotating corpora intended for language learners. In particular, we focus on spoken corpora for being used as complementary material in the classroom as well as in examinations. We describe the three corpora (Spanish, Chinese and Japanese) compiled by the Labor...
Spontaneous Speech Corpora for language learners of Spanish, Chinese and Japanese
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This paper introduces the philosophy of Quality Assurance and traces the development of the British Standard for Quality Systems -BS 5750. The key components of the Quality System are covered and there is a discussion on how to choose a Quality System which is most appropriate to the needs of the particular organisatio...
Translating and the Computer 14
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The approach presented here enables Japanese users with no knowledge of English or legal English to generate patent claims in English from a Japanese-only interface. It exploits the highly determined structure of patent claims and merges Natural Language Generation (NLG) and Machine Translation (MT) techniques and reso...
A Human-Aided Machine Translation System for Japanese-English Patent Translation
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This paper describes the treatment of nominalizations in the PUNDIT text processing system. A single semantic definition is used for both nominalizations and the verbs to which they are related, with the same semantic roles, decompositions, and selectional restrictions on the semantic roles. However, because syntactica...
NOMINALIZATIONS IN PUNDIT
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We present an experimental framework for Entity Mention Detection in which two different classifiers are combined to exploit Data Redundancy attained through the annotation of a large text corpus, as well as a number of Patterns extracted automatically from the same corpus. In order to recognize proper name, nominal, a...
Entity Mention Detection using a Combination of Redundancy-Driven Classifiers
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Supervised training of models for semantic relation extraction has yielded good performance, but at substantial cost for the annotation of large training corpora. Active learning strategies can greatly reduce this annotation cost. We present an efficient active learning framework that starts from a better balance betwe...
An Efficient Active Learning Framework for New Relation Types
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Languages with complex morphologies present difficulties for dictionaries users. One solution to this problem is to use a morphological parser for lookup of morphologically complex words, including fully inflected words, without the user needing to explicitly know the morphology. We discuss the sorts of morphologies wh...
Morphological Interfaces to Dictionaries
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This paper focuses on examining the effect of extra-linguistic information, such as eye gaze, integrated with linguistic information on multi-modal reference resolution. In our evaluation, we employ eye gaze information together with other linguistic factors in machine learning, while in prior work such as Kelleher(200...
Multi-modal Reference Resolution in Situated Dialogue by Integrating Linguistic and Extra-Linguistic Clues
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l~t:ovious work has shown thai adding genera.liza.tion of the exa.ml)les in the corpus of a.n exa.ml)le-1)ased machine tra.nsla.tion (I'31LMT) system ea, n reduce 1;he re(ltfire.d amount o[' pretra.nsla.ted exa.ml)le text l)y as [iltl(;]l }is a.ii order o[' magnitude for Spa.nish-l';nglish and l,'rench-l~;nglish I+',I~...
Automated Generalization of Translation Examples
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Spoken dialogue systems (SDS) are rapidly appearing in various smart devices (smartphone, smart-TV, in-car navigating system, etc). The key role in a successful SDS is a spoken language understanding (SLU) component, which parses user utterances into semantic concepts in order to understand users' intentions. However, ...
Unsupervised Learning and Modeling of Knowledge and Intent for Spoken Dialogue Systems
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An attempt has been made to use an Augmented Transition Network IO as a 'procedural dialog model'. The development of such a model appears to be important in several respects: -as a device to represent and to use different dialog schemata proposed in empirical conversation analysis; -as a device to represent and to use...
ATNS USED AS A PROCEDURAL DIALOG MODEL
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Multi-lingual relation extraction aims to find unknown relational facts from text in various languages. Existing models cannot well capture the consistency and diversity of relation patterns in different languages. To address these issues, we propose an adversarial multi-lingual neural relation extraction (AMNRE) model...
Adversarial Multi-lingual Neural Relation Extraction
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Collocation extraction systems based on pure statistical methods suffer from two major problems. The first problem is their relatively low precision and recall rates. The second problem is their difficulty in dealing with sparse collocations. In order to improve performance, both statistical and lexicographic approache...
Similarity Based Chinese Synonym Collocation Extraction
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Rapid advances in the biomedical field have resulted in the accumulation of numerous experimental results, mainly in text form. To extract knowledge from biomedical papers, or use the information they contain to interpret experimental results, requires improved techniques for retrieving information from the biomedical ...
Gene/protein/family name recognition in biomedical literature
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En reconnaissance de la parole, un des moyens d'améliorer les performances des systèmes est de passer par l'adaptation des modèles de langage. Une étape cruciale de ce processus consiste à détecter le thème du document traité et à adapter ensuite le modèle de langage. Dans cet article, nous proposons une nouvelle appro...
Nouvelle approche de la sélection de vocabulaire pour la détection de thème
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Although Japanese has relatively free word order, Japanese word order is not completely arbitrary and has some sort of preference. Since such preference is incompletely understood, even native Japanese writers often write Japanese sentences which are grammatically well-formed but not easy to read. This paper proposes a...
Japanese Word Reordering Integrated with Dependency Parsing
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Typical sentences of characteristic syntactic structures can be used for language understanding tasks like finding typical slotfiller for verbs. The paper describes the selection of such typical sentences representing usually about 5% of the original corpus. The sentences are selected by the frequency of the correspond...
Corpora of Typical Sentences
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Systems Research and Applications4300 Fair Lakes Court South Building, Suite 50 0 Fairfax, VA 22033-423 2 krupka@sra.comINTRODUCTIO NSRA used the combination of two systems for the MUC-6 tasks : NameTag"" , a commercial software product that recognizes proper names and other key phrases in text ; and HASTEN, an experim...
SRA : Description of the SRA System as Used for MUC-6
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This paper discusses/presents problems of template structure for Information Extraction. We investigate these problems in the context of two new Information Extraction scenarios which are linguistically and structurally more challenging than the traditional MUC scenarios. By a scenario we mean a predefined set of facts...
Diversity of Scenarios in Information Extraction
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This paper describes a project that aims to create a Mandarin speech database for the automobile setting (TAICAR). A group of researchers from several universities and research institutes in Taiwan have participated in the project. The goal is to generate a corpus for the development and testing of various speech-proce...
TAICAR -The Collection and Annotation of an In-Car Speech Database Created in Taiwan