Referenzsemantik in der Partnermodellierung

How can we explain that an assertion on something perceived can be understood in the same manner by somebody who cannot perceive that scene? This problem bases the interest in computational linguistics in how listener modeling could possibly be harmonized with reference semantics. Mental images substituting real perception appear as a way out. The architecture of the listener model has to be adapted to the creation and use of such pictorial data structures. Furthermore, the relation between the latter and a verbal (i. e., propositional) representation must be understood. The resulting architecture of a listener model with reference semantics can be employed to solve communicational problems from three general classes in a better way, as is demonstrated by an example implementation.     

Perception of relative pitch with different references: Some absolute-pitch listeners can’t tell musical interval names

Two experiments were conducted to examine the effect of absolute-pitch possession on relativepitch processing. Listeners attempted to identify melodic intervals ranging from a semitone to an octave with different reference tones. Listeners with absolute pitch showed declined performance when the reference was out-of-tune C, out-of-tune E, or F#, relative to when the reference was C. In contrast, listeners who had no absolute pitch maintained relatively high performance in all reference conditions. These results suggest that absolute-pitch listeners are weak in relative-pitch processing and show a tendency to rely on absolute pitch in relative-pitch tasks.     

Identification of inconsistent variates in factor analysis

When some of observed variates do not conform to the model under consideration, they will have a serious effect on the results of statistical analysis. In factor analysis the model with inconsistent variates may result in improper solutions. In this article a useful method for identifying a variate as inconsistent is proposed in factor analysis. The procedure is based on the likelihood principle. Several statistical properties such as the effect of misspecified hypotheses, the problem of multiple comparisons, and robustness to violation of distributional assumptions are investigated. The procedure is illustrated by some examples.