Knowledge-based disambiguation for machine translation

The resolution of ambiguities is one of the central problems for Machine Translation. In this paper we propose a knowledge-based approach to disambiguation which uses Description Logics (DL) as representation formalism. We present the process of anaphora resolution implemented in the Machine Translation system FAST and show how the DL system BACK is used to support disambiguation. The disambiguation strategy uses factors representing syntactic, semantic, and conceptual constraints with different weights to choose the most adequate antecedent candidate. We show how these factors can be declaratively represented as defaults in BACK. Disambiguation is then achieved by determining the interpretation that yields a qualitatively minimal number of exceptions to the defaults, and can thus be formalized as exception minimization

Dialogue acts in automatic dialogue interpreting

In this paper we demonstrate that for an adequate translation of an utterance spoken in a dialogue the dialogue act it performs has to be determined. We introduce an approach that automatically assigns types of dialogue acts to utterances on the basis of both micro- and macro-structural information. Technically, this assignment is realized by modeling preference rules as weighted defaults in the Description Logic system FLEX. The dialogue-act type of an utterance is determined by qualitatively minimizing the exceptions to these defaults. The results described here have been developed within the VERBMOBIL project, a project concerned with face-to-face dialogue interpreting funded by the German Federal Ministry of Education, Science, Research and Technology (BMBF). We present the rather positive results of a first evaluation of this implementation showing the accuracy of dialogue act assignment

Criteria for the segmentation of spoken input into individual utterances

This report describes how spoken language turns are segmented into utterances in the framework of the verbmobil project. The problem of segmenting turns is directly related to the task of annotating a discourse with dialogue act information: an utterance can be characterized as a stretch of dialogue that is attributed one dialogue act. Unfortunately, this rule in many cases is insufficient and many doubtful cases remain. We tried to at least reduce the number of unclear cases by providing a number of hands-on rules for segmenting dialogues. In that sense, we hope that this document is helpful for labeling dialogues with discourse information. This report has to be seen as an extension of the verbmobil Report No.65 that includes a detailed discussion of the various dialogue act types employed in verbmobil. All dialogue act types used throughout this report are taken from the set defined there

The VERBMOBIL domain model version 1.0

This report describes the domain model used in the German Machine Translation project VERBMOBIL. In order make the design principles underlying the modeling explicit, we begin with a brief sketch of the VERBMOBIL demonstrator architecture from the perspective of the domain model. We then present some rather general considerations on the nature of domain modeling and its relationship to semantics. We claim that the semantic information contained in the model mainly serves two tasks. For one thing, it provides the basis for a conceptual transfer from German to English; on the other hand, it provides information needed for disambiguation. We argue that these tasks pose different requirements, and that domain modeling in general is highly task-dependent. A brief overview of domain models or ontologies used in existing NLP systems confirms this position. We finally describe the different parts of the domain model, explain our design decisions, and present examples of how the information contained in the model can be actually used in the VERBMOBIL demonstrator. In doing so, we also point out the main functionality of FLEX, the Description Logic system used for the modeling

Warming, but Not Acidification, Restructures Epibacterial Communities of the Baltic Macroalga Fucus vesiculosus With Seasonal Variability

Due to ocean acidification and global warming, surface seawater of the western Baltic Sea is expected to reach an average of ∼1100 μatm pCO2 and an increase of ∼5°C by the year 2100. In four consecutive experiments (spanning 10–11 weeks each) in all seasons within 1 year, the abiotic factors temperature (+5°C above in situ) and pCO2 (adjusted to ∼1100 μatm) were tested for their single and combined effects on epibacterial communities of the brown macroalga Fucus vesiculosus and on bacteria present in the surrounding seawater. The experiments were set up in three biological replicates using the Kiel Outdoor Benthocosm facility (Kiel, Germany). Phylogenetic analyses of the respective microbiota were performed by bacterial 16S (V1-V2) rDNA Illumina MiSeq amplicon sequencing after 0, 4, 8, and 10/11 weeks per season. The results demonstrate (I) that the bacterial community composition varied in time and (II) that relationships between operational taxonomic units (OTUs) within an OTU association network were mainly governed by the habitat. (III) Neither single pCO2 nor pCO2:Temperature interaction effects were statistically significant. However, significant impact of ocean warming was detected varying among seasons. (IV) An indicator OTU (iOTU) analysis identified several iOTUs that were strongly influenced by temperature in spring, summer, and winter. In the warming treatments of these three seasons, we observed decreasing numbers of bacteria that are commonly associated with a healthy marine microbial community and—particularly during spring and summer—an increase in potentially pathogenic and bacteria related to intensified microfouling. This might lead to severe consequences for the F. vesiculosus holobiont finally affecting the marine ecosystem

Dialogue acts in Verbmobil 2

This report describes the dialogue phases and the second edition dialogue acts which are used in the VERBMOBIL 2 project [...]. While in the first project phase the scenario was restricted to appointment scheduling dialogues, it has been extended to travel planning in the second phase with appointment scheduling being only a part of the new scenario