Articles

Word processors or computers used in Japan employ Japanese input method through key- board stroke combined with Kana (phonetic) character to Kanji (ideographic, Chinese) char- acter conversion technology. The key factor of Kana-to-Kanji conversion technology is how to raise the accuracy of the conversion through the homophone processing, since we …...

In this paper wc discuss the use of discourse con- text in spoken dialogue systems and argue that the knowledge of the domain, modelled with the help of dialogue topics is important in maintaining robust- hess of the system and improving recognition accu- racy of spoken utterances. We propose a …...

In this paper I will report the result of a quan- titative analysis of the dynamics of the con- stituent elements of Japanese terminology. In Japanese technical terms, the linguistic contri- bution of morphemes greatly differ according to their types of origin. To analyse this aspect, a quantitative method is …...

In order to realize their full potential, multimodal systems need to support not just input from multiple modes, but also synchronized integration of modes. Johnston et al (1997) model this integration using a unification opera- tion over typed feature structures. This is an effective so- lution for a broad class …...

This paper describes how to construct a finite-state machine (FSM) approximating a 'unification-based' grammar using a left-corner grammar transform. The approximation is presented as a series of gram- mar transforms, and is exact for leftqinear and right- linear CFGs, and for trees up to a user-specified depth of center-embedding. 1...

A method is presented for segmenting text into subtopic areas. The proportion of related pairwise words is calculated between adjacent windows of text to determine their lexical similarity. The lexical cohesion relations of reiteration and collocation are used to identify related words. These relations are automatically located using a combination …...

A lexicon is an essential component in a gener- ation system but few efforts have been made to buiht a rich, large-scale lexicon and make it reusable for different generation applications. In this paper, we describe our work to build 'inch a lexicon by combining multiple, heteroge- neous linguistic resources …...

In this paper, we study the problem of combining a Chinese thesaurus with a Chinese dictionary by linking the word entries in the thesaurus with the word senses in the dictionary, and propose a similar word strategy to solve the problem. The method is based on the definitions given in …...

This paper looks at representing para- phrases using the formalism of Syn- chronous TAGs; it looks particularly at comparisons with machine translation and the modifications it is necessary to make to Synchronous TAGs for paraphrasing. A more detailed version is in Dras (1997a). 1...

This paper presents a partial solution to a com- ponent of the problem of lexical choice: choos- ing the synonym most typical, or expected, in context. We apply a new statistical approach to representing the context of a word through lexical co-occurrence networks. The imple- mentation was trained and evaluated …...

We describe the early stage of our method- ology of knowledge acquisition from techni- cal texts. First, a partial morpho-syntactic analysis is performed to extract "candi- date terms". Then, the knowledge engi- neer, assisted by an automatic clustering tool, builds the "conceptual fields" of the domain. We focus on this …...

The information used for the extraction of terms can be considered as rather 'inter- nal', i.e. coming from the candidate string itself. This paper presents the incorpora- tion of 'external' information derived from the context of the candidate string. It is embedded to the C-value approach for automatic term recognition …...

The paper presents a language model that develops syntactic structure and uses it to extract meaningful information from the word history, thus enabling the use of long distance dependencies. The model as- signs probability to every joint sequence of words-binary-parse-structure with head- word annotation. The model, its proba- bilistic parametrization, …...

Many multilingual NLP applications need to translate words between different lan- guages, but cannot afford the computa- tional expense of inducing or applying a full translation model. For these applications, we have designed a fast algorithm for esti- mating a partial translation model, which accounts for translational equivalence only at …...

We present a knowledge and context-based system for parsing and translating natu- ral language and evaluate it on sentences from the Wall Street Journal. Applying machine learning techniques, the system uses parse action examples acquired un- der supervision to generate a determinis- tic shift-reduce parser in the form of a …...

This paper shows that a class of Combinatory Categorial Grammars (CCGs) augmented with a linguistically-motivated form of type raising involving variables is weakly equivalent to the standard CCGs not involving variables. The proof is based on the idea that any instance of such a grammar can be simulated by a …...

In this paper, we describe a method for automatically retrieving collocations from large text corpora. This method retrieve collocations in the following stages: 1) ex- tracting strings of characters as units of collocations 2) extracting recurrent combi- nations of strings in accordance with their word order in a corpus as …...

This paper describes the conversion of a Hidden Markov Model into a sequential transducer that closely approximates the behavior of the stochastic model. This transformation is especially advantageous for part-of-speech tagging because the re- sulting transducer can be composed with other transducers that encode correction rules for the most frequent …...

String transformation systems have been introduced in (Brill, 1995) and have sev- eral applications in natural language pro- cessing. In this work we consider the com- putational problem of automatically learn- ing from a given corpus the set of transfor- mations presenting the best evidence. We introduce an original data …...

This paper analyses the relation between the use of similarity in Memory-Based Learning and the notion of backed-off smoothing in statistical language model- ing. We show that the two approaches are closely related, and we argue that feature weighting methods in the Memory-Based paradigm can offer the advantage of au- …...