| The LNAI series reports state-of-the-art results in artificial intelligence re-search, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies,LNAI has grown into the most comprehensive artificial intelligence research forum available. The scope of LNAI spans the whole range of artificial intelligence and intelli-gent information processing including interdisciplinary topics in a variety of application fields. The type of material published traditionally includes. -proceedings (published in time for the respective conference) -post-proceedings (consisting of thoroughly revised final full papers) -research monographs (which may be based on PhD work) |
| Invited Talks Combating the Sparse Data Problem of Language Modelling Toward Robust Speech Recognition and Understanding Text A Pilot Study of English Selectional Preferences and Their Cross-Lingual Compatibility with Basque Auto-tagging of Text Documents into XML Stable Coordinated Pairs in Text Processing Backoff DOP: Parameter Estimation by Backoff Document Clustering into an Unknown Number of Clusters Using a Genetic Algorithm Experiments in German Treebank Parsing A Theoretical Basis of an Architecture of a Shell of a Reasonably Robust Syntactic Analyser Si3Trenn and Si3Silb: Using the SiSiSi Word Analysis System for Pre-hyphenation and Syllable Counting in German Documents Detecting Annotation Errors in a Corpus by Induction of Syntactic Patterns The Computational Complexity of Rule-Based Part-of-Speech Tagging Text Corpus with Errors Identification of Multiwords as Preprocessing for Automatic Extraction of Lexical Similarities Build a Large-Scale Syntactically Annotated Chinese Corpus Computational Benefits of a Totally Lexicalist Grammar Using a Czech Valency Lexicon for Annotation Support On Concept Based Approach for Determining Semantic Index Terms Corpora Issues in Validation of Serbian Wordnet Optimising Attribute Selection in Conversational Search Russian Corpus of the 19th Century Speech On Homogeneous Segments Advances in Automatic Speech Recognition by Imitating Spreading Activation.. The Incorporation of Confidence Measures to Language Understanding Speech Recognition with #-Law Companded Features on Reverberated Signals . Understanding Speech Based on a Bayesian Concept Extraction Method A Data-Driven Framework for Intonational Phrase Break Prediction Phoneme Recognition Using Temporal Patterns …… Dialogue Author Index |
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