3,391 research outputs found
Integrated speech and morphological processing in a connectionist continuous speech understanding for Korean
A new tightly coupled speech and natural language integration model is
presented for a TDNN-based continuous possibly large vocabulary speech
recognition system for Korean. Unlike popular n-best techniques developed for
integrating mainly HMM-based speech recognition and natural language processing
in a {\em word level}, which is obviously inadequate for morphologically
complex agglutinative languages, our model constructs a spoken language system
based on a {\em morpheme-level} speech and language integration. With this
integration scheme, the spoken Korean processing engine (SKOPE) is designed and
implemented using a TDNN-based diphone recognition module integrated with a
Viterbi-based lexical decoding and symbolic phonological/morphological
co-analysis. Our experiment results show that the speaker-dependent continuous
{\em eojeol} (Korean word) recognition and integrated morphological analysis
can be achieved with over 80.6% success rate directly from speech inputs for
the middle-level vocabularies.Comment: latex source with a4 style, 15 pages, to be published in computer
processing of oriental language journa
Identification of Fertile Translations in Medical Comparable Corpora: a Morpho-Compositional Approach
This paper defines a method for lexicon in the biomedical domain from
comparable corpora. The method is based on compositional translation and
exploits morpheme-level translation equivalences. It can generate translations
for a large variety of morphologically constructed words and can also generate
'fertile' translations. We show that fertile translations increase the overall
quality of the extracted lexicon for English to French translation
Incorporation of two terminology projects into a system for information retrieval using NLP for term expansion
In this paper, we will discuss two medical terminology projects at the University College of Ghent, Faculty of translation studies, and the benefits of combining them to provide Dutch professionals and laymen with better access to information in biomedical databases. Our first project, the MeSH Termbase Project (MTB) is aimed at health care professionals, medical translators and also patients in need of language support. The main aim of our second project, the Multilingual Glossary of Technical and Popular Medical Terms, is the simplification of the terminology used in patient information leaflets
Enriching ontological user profiles with tagging history for multi-domain recommendations
Many advanced recommendation frameworks employ ontologies of various complexities to model individuals and items, providing a mechanism for the expression of user interests and the representation of item attributes. As a result, complex matching techniques can be applied to support individuals in the discovery of items according to explicit and implicit user preferences. Recently, the rapid adoption of Web2.0, and the proliferation of social networking sites, has resulted in more and more users providing an increasing amount of information about themselves that could be exploited for recommendation purposes. However, the unification of personal information with ontologies using the contemporary knowledge representation methods often associated with Web2.0 applications, such as community tagging, is a non-trivial task. In this paper, we propose a method for the unification of tags with ontologies by grounding tags to a shared representation in the form of Wordnet and Wikipedia. We incorporate individuals' tagging history into their ontological profiles by matching tags with ontology concepts. This approach is preliminary evaluated by extending an existing news recommendation system with user tagging histories harvested from popular social networking sites
SKOPE: A connectionist/symbolic architecture of spoken Korean processing
Spoken language processing requires speech and natural language integration.
Moreover, spoken Korean calls for unique processing methodology due to its
linguistic characteristics. This paper presents SKOPE, a connectionist/symbolic
spoken Korean processing engine, which emphasizes that: 1) connectionist and
symbolic techniques must be selectively applied according to their relative
strength and weakness, and 2) the linguistic characteristics of Korean must be
fully considered for phoneme recognition, speech and language integration, and
morphological/syntactic processing. The design and implementation of SKOPE
demonstrates how connectionist/symbolic hybrid architectures can be constructed
for spoken agglutinative language processing. Also SKOPE presents many novel
ideas for speech and language processing. The phoneme recognition,
morphological analysis, and syntactic analysis experiments show that SKOPE is a
viable approach for the spoken Korean processing.Comment: 8 pages, latex, use aaai.sty & aaai.bst, bibfile: nlpsp.bib, to be
presented at IJCAI95 workshops on new approaches to learning for natural
language processin
- …