Sprache im 20. Jahrhundert. Gegenwartssprache
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Whether verbs have to be marked as punctual vs. durative has been a controversial issue from the very beginnings of research on aktionsarten in the last century right on up to modern theories of aspectual classes and aspect composition. Debates about the linguistic necessity of this distinction have often been accompanied by the question of what it means for a verb to be temporally punctual. In this paper I will, firstly, sketch the history of research on the punctual-durative distinction and present several linguistic arguments in its favor. Secondly, I will show how this distinction is captured in an eventstructure- based approach to lexical semantics. Thirdly, I will discuss the extent to which a precise definition of the notions used in lexical
representations helps avoid circular argumentation in lexical semantics. Finally, I will demonstrate how this can be done for the notion of ‘punctuality’ by clarifying the logical type of this predicate and relating it to central cognitive time concepts.
The aim of this paper is to highlight the actual need for corpora that have been annotated based on acoustic information. The acoustic information should be coded in features or properties and is needed to inform further processing systems, i.e. to present a basis for a speech recognition system using linguistic information. Feature annotation of existing corpora in combination with segmental annotation can provide a powerful training material for speech recognition systems, but will as well challenge the further processing of features to segments and syllables. We present here the theoretical preliminaries for our multilingual feature extraction system, that we are currently working on.
Both for psychology and linguistics, emotion concepts are a continuing challenge for analysis in several respects. In this contribution, we take up the language of emotion as an object of study from several angles. First, we consider how frame semantic analyses of this domain by the FrameNet project have been developing over time, due to theory-internal as well as application-oriented goals, towards ever more fine-grained distinctions and greater within-frame consistency. Second, we compare how FrameNet’s linguistically oriented analysis of lexical items in the emotion domain compares to the analysis by domain experts of the experiences that give rise (directly or indirectly) to the lexical items. And finally, we consider to what extent frame semantic analysis can capture phenomena such as connotation and inference about attitudes, which are important in the field of sentiment analysis and opinion mining, even if they do not involve the direct evocation of emotion.