Naturalness

About: Naturalness is a research topic. Over the lifetime, 1305 publications have been published within this topic receiving 31737 citations.

A "natural" lexicalization model for language generation

Abstract: We propose a general lexicalization model which accounts for how lexical units are selected and introduced in linguistic utterances during language generation. This model aims at “naturalness” by being based on actual lexical knowledge used in speech; consequently, it should be compatible with standard patterns of behavior shown by humans when they speak (flexibility in computing both content and form of linguistic utterances, prototypical types of mistakes and backtracking, etc.). The main advantage of our model, once implemented in automatic language generation, is that it takes into account fundamental differences that exist between lexical units, with regard to why and how they are used in texts. This is achieved by means of a stratificational approach to lexicalization, where each type of lexical unit is introduced at a proper level of representation, according to the role it plays in the enunciation. Section 1 offers a general characterization of the approach and makes explicit its main assumptions. Sections 2 to 4 successively examine the three levels of transition implied by the stratificational structuring of the model. Section 5 concludes with an examination of its relevance to the design of text generation systems.

Influence of chroma variations on naturalness and image quality of stereoscopic images

Abstract: The computational view on image quality of Janssen and Blommaert states that the quality of an image is determined by the degree to which the image is both useful (discriminability) and natural (identifiability). This theory is tested by creating two manipulations. Firstly, multiplication of the chroma values of each pixel with a constant in the CIELab color space, i.e., chroma manipulation, is expected to increase only the usefulness by increasing the distances between the individual color points, enhancing the contrast. Secondly, introducing stereoscopic depth by varying the screen disparity, i.e., depth manipulation, is expected to increase both the usefulness and the naturalness. Twenty participants assessed perceived image quality, perceived naturalness and perceived depth of the manipulated versions of two natural scenes. The results revealed a small, yet significant shift between image quality and naturalness as a function of the chroma manipulation. In line with previous research, preference in quality was shifted to higher chroma values in comparison to preference in naturalness. Introducing depth enhanced the naturalness scores, however, in contrast to our expectations, not the image quality scores. It is argued that image quality is not sufficient to evaluate the full experience of 3D. Image quality appears to be only one of the attributes underlying the naturalness of stereoscopic images.

Color preference and perceived color naturalness of digital videos

Abstract: In this study, we examined the subjective attributes of color preference and perceived naturalness of digital videos when the chroma of the color content was varied. More specifically, the objectives were: (1) to determine how the scaling of color chroma affected the mean color preference rating and the mean naturalness rating across subjects and (2) to determine how preference and naturalness were related. To this end, psychophysical experiments were carried out in which naive subjects provided us with their subjective assessments of these two attributes. Data from the experiments indicated that for both preference and naturalness, the mean opinion scores (MOS) increased to a maximum and decreased as the mean chroma (MC) of the videos was varied. Naturalness MOS (NMOS) tended to reach a maximum at lower MC than preference MOS (PMOS). The maximums for both PMOS and NMOS occurred at relatively close MC levels for most of the videos. The individual functions relating MOS to chroma were modeled by simple Gaussian functions relatively well. However, the mean, amplitude and standard deviation varied with video. It was possible to reduce the total number of parameters from 36 to 15 parameters by making use of relationships between the model parameters. In this model the chroma corresponding to maximum preference is about 1.1 times the chroma corresponding to maximum naturalness.

Bayesian Study and Naturalness in MSSM Forecast for the LHC

Abstract: We perform a forecast of the CMSSM for the LHC based in an improved Bayesian analysis taking into account the present theoretical and experimental wisdom about the model. In this way we obtain a map of the preferred regions of the CMSSM parameter space and show that fine-tuning penalization arises from the Bayesian analysis itself when the experimental value of Mz is considered. The results are remarkable stable when using different priors