waashk/dblp huggingface dataset:
linguistic processing using a dependency structure grammar for speech recognition and understanding. this paper proposes an efficient linguistic processing strategy for speech recognition and understanding using a dependency structure grammar. the strategy includes parsing and phrase prediction algorithms. after speech processing and phrase recognition based on phoneme recognition, the parser extracts the sentence with the best likelihood taking account of the phonetic likelihood of phrase candidates and the linguistic likelihood of the semantic inter-phrase dependency relationships. a fast parsing algorithm using breadth-first search is also proposed. the predictor pre-selects the phrase candidates using transition rules combined with a dependency structure to reduce the amount of phonetic processing. the proposed linguistic processor has been tested through speech recognition experiments. the experimental results show that it greatly increases the accuracy of speech recognitions, and the breadth-first parsing algorithm and predictor increase processing speed.
two approaches to semantic interfaces in text generation. this paper is a contribution towards the exploration of semantic interfaces in text generation systems. it suggests a general interpretation of semantics for the purpose of text generation as an interlevel between lexicogrammar (the resources of grammar and vocabulary) and higher levels of organization (knowledge base, user model, text planning, and so on). two approaches to the design of this interlevel that have been implemented in generation systems are then presented -- chooser & inquiry semantics and situation-specific semantic systems. they are compared and contrasted to bring out their relative merits.
semantic rule based text generation. this paper presents a semantically oriented, rule based method for single sentence text generation and discusses its implementation in the kafka generator. this generator is part of the xcalibur natural language interface developed at cmu to provide natural language facilities for a wide range of expert systems and data bases. kafka takes as input the knowledge representation used in xcalibur system and incrementally transforms it first into conceptual dependency graphs and then into english.1
b-sure: a believed situation and uncertain-action representation environment. this paper presents a system that is capable of representing situations, states, and nondeterministic nonmonotonic-outcome actions occurring in multiple possible worlds. the system supports explicit representations of actions and situations used in intentional action theory and situation theory. both types and instances are supported. situations and states before and after nonmonotomic actions can be represented simultaneously. agents have free will as to whether to choose to perform an action or not. situations and actions can have expected values, allowing the system to support decision-making and decision-based plan inferencing. the system can perform global reasoning simultaneously across multiple possible worlds, without being forced to extend each world explicitly. the resulting system is useful for such natural language tasks as plan recognition, intentions modeling, and parallel task scheduling.
a new formal tool: functorial variables representing assertions and presuppositions. the language of classical propositional logic is extended by <u>functorial variables</u> as a new syntactical category. functorial variables render to be a possible integrating representation of both assertion and presupposition in one and the same logical formula different from such using classical conjunction.
annotating topological fields and chunks - and revising pos tags at the same time. annotating a corpus of german with chunks, topological fields and clause boundaries is both a goal in itself and a step towards further syntactic annotation. partial annotation can serve as data to test linguistic hypotheses and it can be used as a pre-structuring for further linguistic annotation steps. if, however, the underlying part-of-speech (pos) annotation is imperfect, these errors will be passed on to the subsequent levels of annotation and increase annotation errors on those levels. it is especially damaging for subsequent annotation if pos tags are incorrect which provide the framework of the german sentence by demarcating the topological fields and the clause boundaries (e.g. subordinators and verbs). this paper presents a method to automatically annotate a corpus of german with chunks, topological fields and clause boundaries, and improve tagging accuracy at the same time in order to increase the overall annotation accuracy. tag improvement primarily relies on the linguistic knowledge encoded in the grammar for annotating the topological fields.
identifying terms by their family and friends. multi-word terms are traditionally identified using statistical techniques or, more recently, using hybrid techniques combining statistics with shallow linguistic information. approaches to word sense disambiguation and machine translation have taken advantage of contextual information in a more meaningful way, but terminology has rarely followed suit. we present an approach to term recognition which identifies salient parts of the context and measures their strength of association to relevant candidate terms. the resulting list of ranked terms is shown to improve on that produced by traditional methods, in terms of precision and distribution, while the information acquired in the process can also be used for a variety of other applications, such as disambiguation, lexical tuning and term clustering.
domain dependent natural language understanding. a natural language understanding system for a restricted domain of discourse - thermodynamic exercises at an introductory level - is presented. the system transforms texts into a formal meaning representation language based on cases. the semantical interpretation of sentences and phrases is controlled by case frames formulated around verbs and surface grammatical roles in noun phrases. during the semantical interpretation of a text, semantic constraints may be imposed on elements of the text. each sentence is analysed with respect to context making the system capable of solving anaphoric references such as definite descriptions, pronouns and elliptic constructions.the system has been implemented and succesfully tested on a selection of exercises.
surface analysis of queries directed toward a database. a natural language interface is directed toward the database query languages that access machine stored data. a pattern driven transformation mechanism supports natural language access. a natural language is mapped onto a more formal computer database language. a human-like "understanding" of the query statement is not required. the transformation mechanism is separate from the target database management system. a goal is independence from both domain content and dbms implementation. there is an emphasis on surface over content analysis.two particular questions are at issue. first, the extent to which a natural language interface to a database may operate independent of the subject domain of the database. specifically, the extent to which natural language queries can be evaluated without the use of a query world descriptive reference system. second, the extent to which natural language queries can be analyzed using pattern recognition techniques.
the treatment of scope and negation in rosetta. this paper deals with the treatment of scope and, in particular, negation in rosetta, a machine translation system which translates between dutch, english and spanish (spanish only as a target language). it will be argued that the sov- versus svo-character of a language has important consequences for its possibilities of reflecting scope through word order. a description will be given of the problems that arise translating from one type of language (the sov-language dutch) to the other (the svo-languages english and spanish). the extent to which these problems can be solved will be outlined.the paper has been divided into two main sections. in section one the phenomena are described linguistically, in section two a general idea is given of how these phenomena are dealt with in rosetta.
correcting object-related misconceptions: how should the system respond? this paper describes a computational method for correcting users' misconceptions concerning the objects modelled by a computer system. the method involves classifying object-related misconceptions according to the knowledge-base feature involved in the incorrect information. for each resulting class sub-types are identified, according to the structure of the knowledge base, which indicate what information may be supporting the misconception and therefore what information to include in the response. such a characterization, along with a model of what the user knows, enables the system to reason in a domain-independent way about how best to correct the user.
on a semantic model for multi-lingual paraphrasing. the aim of the present paper is to formalize semantic-directed lexical selection by virtue of frame-based semantic inference capability built in the cfl representation language. the dg model of paraphrasing semantic descriptions can explicate logical process of knowledge-based sentence generation excluding any particular procedures for lexical selection or syntax structure generation. in addition this paper emphasises that this model is basically not dependent on target languages.
analyzing japanese double-subject construction having an adjective predicate. this paper describes a method for analyzing japanese double-subject construction having an adjective predicate based on the valency structure. a simple sentence usually has only one subjective case in most languages. however, many japanese adjectives (and some verbs) can dominate two surface subjective cases within a simple sentence. such sentence structure is called the double-subject construction. this paper classifies the japanese double-subject construction into four types and describes problms arising when analyzing these types using ordinary japanese construction approaches. this paper proposes a method for analyzing a japanese double-subject construction having an adjective predicate in order to overcome the problems described. by applying this method to japanese sentence analysis in. japanese-to-english machine translation systems, translation accuracy can be improved because this method can analyze correctly the double-subject construction.
logic compression of dictionaries for multilingual spelling checkers. to provide practical spelling checkers on micro-computers, good compression algorithms are essential. current techniques used to compress lexicons for indo-european languages provide efficient spelling checker. applying the same methods to languages which have a different morphological system (arabic, turkish,...) gives insufficient results. to get better results, we apply other "logical" compression mechanisms based on the structure of the language itself. experiments with multilingual dictionaries show a significant reduction rate attributable to our logic compression alone and even better results when using our method in conjunction with existing methods.
bunsetsu identification using category-exclusive rules. this paper describes two new bunsetsu identification methods using supervised learning. since japanese syntactic analysis is usually done after bunsetsu identification, bunsetsu identification is important for analyzing japanese sentences. in experiments comparing the four previously available machine-learning methods (decision tree, maximum-entropy method, example-based approach and decision list) and two new methods using category-exclusive rules, the new method using the category-exclusive rules with the highest similarity performed best.
hierarchical orderings of textual units. text representation is a central task for any approach to automatic learning from texts. it requires a format which allows to interrelate texts even if they do not share content words, but deal with similar topics. furthermore, measuring text similarities raises the question of how to organize the resulting clusters. this paper presents cohesion trees (ct) as a data structure for the perspective, hierarchical organization of text corpora. cts operate on alternative text representation models taking lexical organization, quantitative text characteristics, and text structure into account. it is shown that cts realize text linkages which are lexically more homogeneous than those produced by minimal spanning trees.
discontinuities in narratives. this paper is concerned with heuristics for segmenting narratives into units that form the basic elements of discourse representations and the constrain the application of focusing algorithms. the following classes of discontinuities are identified: figure-groud, space, time, perspective, and topic. it is suggested that rhetorical relations between narrative units are macro labels that stand for frequently occurring clusters of discontinuities. heuristics for identifying discontinuities are presented and illustrated in an extended example.
lexical transfer: between a source rock and a hard target. lexical transfer is the point of transition between an unchangeable source text (a rock) and an infinite array of target texts (a hard place to find an acceptable one). the author's coling86 paper (pp. 104--106) described a new methodology for testing lexical transfer in machine translation. this paper reports on the application of that methodology to a test of the dlt system and describes a synchronized bilingual data base by-product. further use of the methodology is encouraged.
interlanguage signs and lexical transfer errors. a theory of interlanguage (il) lexicons is outlined, with emphasis on il lexical entries, based on the hpsg notion of lexical sign. this theory accounts for idiosyncratic or lexical transfer of syntactic subcategorisation and idioms from the first language to the il. it also accounts for developmental stages in il lexical grammar, and grammatical variation in the use of the same lexical item. the theory offers a tool for robust parsing of lexical transfer errors and diagnosis of such errors.
dependency analyzer: a knowledge-based approach to structural disambiguation. to resolve structural ambiguities in syntactic analysis of natural language, which are caused by prepositional phrase attachment, relative clause attachment, and so on, we developed an experimental system called the dependency analyzer. the system uses instances of dependency structures extracted from a terminology dictionary as a knowledge base. structural (attachment) ambiguity is represented by showing that a word has several words as candidate modifiees. the system resolves such ambiguity as follows first, it searches the knowledge base for modification relationships (dependencies) between the word and each of its possible modifiees, then assigns an order of preference to these relationships, and finally selects the most preferable dependency. the knowledge base can be constructed semi-automatically, since the source of knowledge exists in the form of texts, and these sentences can be analyzed by the parser and transformed into dependency structures by the system. we are realizing knowledge bootstrapping by adding the outputs of the system to its knowledge base.
a new method of n-gram statistics for large number of n and automatic extraction of words and phrases from large text data of japanese. in the process of establishing the information theory, c. e. shannon proposed the markov process as a good model to characterize a natural language. the core of this idea is to calculate the frequencies of strings composed of n characters (n-grams), but this statistical analysis of large text data and for a large n has never been carried out because of the memory limitation of computer and the shortage of text data. taking advantage of the recent powerful computers we developed a new algorithm of n-grams of large text data for arbitrary large n and calculated successfully, within relatively short time, n-grams of some japanese text data containing between two and thirty million characters. from this experiment it became clear that the automatic extraction or determination of words, compound words and collocations is possible by mutually comparing n-gram statistics for different values of n.
annotation-based multimedia summarization and translation. this paper presents techniques for multimedia annotation and their application to video summarization and translation. our tool for annotation allows users to easily create annotation including voice transcripts, video scene descriptions, and visual/auditory object descriptions. the module for voice transcription is capable of multilingual spoken language identification and recognition. a video scene description consists of semi-automatically detected keyframes of each scene in a video clip and time codes of scenes. a visual object description is created by tracking and interactive naming of people and objects in video scenes. the text data in the multimedia annotation are syntactically and semantically structured using linguistic annotation. the proposed multimedia summarization works upon a multimodal document that consists of a video, keyframes of scenes, and transcripts of the scenes. the multimedia translation automatically generates several versions of multimedia content in different languages.
an english japanese machine translation system of the titles of scientific and engineering papers. the title sentences of scientific and engineering papers are analyzed by simple parsing strategies, and only eighteen fundamental sentential structures are obtained from ten thousand titles. title sentences of physics and mathematics of some databases in english are translated into japanese with their keywords, author names, journal names and so on by using these fundamental structures. the translation accuracy for the specific areas of physics and mathematics from inspec database was about 93%.
an empirical study on rule granularity and unification interleaving toward an efficient unification-based parsing system. this paper describes an empirical study on the optimal granularity of the phrase structure rules and the optimal strategy for interleaving cfg parsing with unification in order to implement an efficient unification-based parsing system. we claim that using "medium-grained" cfg phrase structure rules, which balance the computational cost of cfg parsing and unification, are a cost-effective solution for making unification-based grammar both efficient and easy to maintain. we also claim that "late unification", which delays unification until a complete cfg parse is found, saves unnecessary copies of dags for irrelevant subparses and improves performance significantly. the effectiveness of these methods was proved in an extensive experiment. the results show that, on average, the proposed system parses 3.5 times faster than our previous one. the grammar and the parser described in this paper are fully implemented and used as the japanese analysis module in sl-trans, the speech-to-speech translation system of atr.
a stochastic japanese morphological analyzer using a forward-dp backward-a* n-best search algorithm. we present a novel method for segmenting the input sentence into words and assigning parts of speech to the words. it consists of a statistical language model and an efficient two-pass n-best search algorithm. the algorithm does not require delimiters between words. thus it is suitable for written japanese. the proposed japanese morphological analyzer achieved 95.1% recall and 94.6% precision for open text when it was trained and tested on the atr corpus.
context-based spelling correction for japanese ocr. we present a novel spelling correction method for those languages that have no delimiter between words, such as japanese, chinese, and thai. it consists of an approximate word matching method and an n-best word segmentation algorithm using a statistical language model. for ocr errors, the proposed word-based correction method outperforms the conventional character-based correction method. when the baseline character recognition accuracy is 90%, it achieves 96.0% character recognition accuracy and 96.3% word segmentation accuracy, while the character recognition accuracy of character-based correction is 93.3%.
zero pronouns as experiencer in japanese discourse. the process of finding the antecedent of zero pronoun, that is indispensable to japanese language understanding, is the topic of this paper. here we mainly concern with discourses comprising two sentences that are in a subordinate relation, especially one of them describes the agent's volitional action and the other describes the reason of the action. we propose basically two new principles: (1) the agent of an action should experience a certain psychological reason, (2) predicates reporting someone's psychological state are categorized into 1) weakly or 2) strongly bound to the expected point of view. combination of these principles accounts for some problematic japanese zero anaphora, which cannot be accounted for by the theories so far proposed.
detecting errors in corpora using support vector machines. while the corpus-based research relies on human annotated corpora, it is often said that a non-negligible amount of errors remain even in frequently used corpora such as penn treebank. detection of errors in annotated corpora is important for corpus-based natural language processing. in this paper, we propose a method to detect errors in corpora using support vector machines (svms). this method is based on the idea of extracting exceptional elements that violate consistency. we propose a method of using svms to assign a weight to each element and to find errors in a pos tagged corpus. we apply the method to english and japanese pos-tagged corpora and achieve high precision in detecting errors.
a parser based on connectionist model. this paper proposes a parser based fully upon the connectionist model(called "cm parser" here after). in order to realize the cm parser, we use sigma-pi-units to implement a constraint of grammatical category order or word order, and a copy mechanism of sub-parse trees. further more, we suppose there exist weak suppressive connection links between every pair of cm units. by these suppressive links, our cm parser explains why garden path sentences and/or deeply nested sentences are hard to recognize. our cm parser also explains the preference principles for syntactically ambiguous sentences.
semantics of complex sentences in japanese. the important part of semantics of complex sentence is captured as relations among semantic roles in subordinate and main clause respectively. however if there can be relations between every pair of semantic roles, the amount of computation to identify the relations that hold in the given sentence is extremely large. in this paper, for semantics of japanese complex sentence, we introduce new pragmatic roles called observer and molivated respectively to bridge sementic roles of subordinate and those of main clauses. by these new roles constraints on the relations among semantic/pragmatic roles are known to be almost local within subordinate or main clause. in other words, as for the semantics of the whole complex sentence, the only role we should deal with is a molivated.