4,565 research outputs found
Estimating Speaking Rate by Means of Rhythmicity Parameters
In this paper we present a speech rate estimator based on so-called rhythmicity features derived from a modified version of the short-time energy envelope. To evaluate the new method, it is compared to a traditional speech rate estimator on the basis of semi-automatic segmentation. Speech material from the Alcohol Language Corpus (ALC) covering intoxicated and sober speech of different speech styles provides a statistically sound foundation to test upon. The proposed measure clearly correlates with the semi-automatically determined speech rate and seems to be robust across speech styles and speaker states
Reputation, Price, and Death: An Empirical Analysis of Art Price Formation
We analyze how an artistâs death influences the market prices of her works of art. Death has two opposing effects on art prices. By irrevocably restricting the artistâs oeuvre, prices, ceteris paribus, increase when the artist dies. On the other hand, an untimely death may well frustrate the collectorsâ hopes of owning artwork that will, as the artistâs career progresses, become generally known and appreciated. By frustrating expected future name recognition, death impacts negatively on art prices. In conjunction, these two channels of influence give rise to a hump-shaped relationship between age at death and death-induced price changes. Using transactions from fine art auctions, we show that the empirically identified death effects indeed conform to our theoretical predictions. We derive our results from hedonic art price regressions, making use of a data set which exceeds the sample size of traditional studies in cultural economics by an order of magnitude.art price formation, death effect, durable goods monopoly
Phenomenology of dark energy: exploring the space of theories with future redshift surveys
We use the effective field theory of dark energy to explore the space of
modified gravity models which are capable of driving the present cosmic
acceleration. We identify five universal functions of cosmic time that are
enough to describe a wide range of theories containing a single scalar degree
of freedom in addition to the metric. The first function (the effective
equation of state) uniquely controls the expansion history of the universe. The
remaining four functions appear in the linear cosmological perturbation
equations, but only three of them regulate the growth history of large scale
structures. We propose a specific parameterization of such functions in terms
of characteristic coefficients that serve as coordinates in the space of
modified gravity theories and can be effectively constrained by the next
generation of cosmological experiments. We address in full generality the
problem of the soundness of the theory against ghost-like and gradient
instabilities and show how the space of non-pathological models shrinks when a
more negative equation of state parameter is considered. This analysis allows
us to locate a large class of stable theories that violate the null energy
condition (i.e. super-acceleration models) and to recover, as particular
subsets, various models considered so far. Finally, under the assumption that
the true underlying cosmological model is the Cold Dark Matter
(CDM) scenario, and relying on the figure of merit of EUCLID-like
observations, we demonstrate that the theoretical requirement of stability
significantly narrows the empirical likelihood, increasing the discriminatory
power of data. We also find that the vast majority of these non-pathological
theories generating the same expansion history as the CDM model
predict a different, lower, growth rate of cosmic structures.Comment: v1: 28 pages, 20 pdf figures. v2: 29 pages, minor improvements in the
text, figures improve
Probing non-standard gravity with the growth index: a background independent analysis
Measurements of the growth index provide a clue as to whether
Einstein's field equations encompass gravity also on large cosmic scales, those
where the expansion of the universe accelerates. We show that the information
encoded in this function can be satisfactorily parameterized using a small set
of coefficients in such a way that the true scaling of the growth
index is recovered to better than in most dark energy and dark gravity
models. We find that the likelihood of current data is maximal for
and , a measurement compatible
with the CDM predictions. Moreover data favor models predicting
slightly less growth of structures than the Planck LambdaCDM scenario. The main
aim of the paper is to provide a prescription for routinely calculating, in an
analytic way, the amplitude of the growth indices in relevant
cosmological scenarios, and to show that these parameters naturally define a
space where predictions of alternative theories of gravity can be compared
against growth data in a manner which is independent from the expansion history
of the cosmological background. As the standard -plane provides a tool
to identify different expansion histories and their relation to various
cosmological models, the -plane can thus be used to locate different
growth rate histories and their relation to alternatives model of
gravity. As a result, we find that the Dvali-Gabadadze-Porrati gravity model is
rejected with a confidence level. By simulating future data sets, such
as those that a Euclid-like mission will provide, we also show how to tell
apart LambdaCDM predictions from those of more extreme possibilities, such as
smooth dark energy models, clustering quintessence or parameterized
post-Friedmann cosmological models.Comment: 29 pages, 21 figure
Laying the Foundation for In-car Alcohol Detection by Speech
The fact that an increasing number of functions in the automobile are and will be controlled by speech of the driver rises the question whether this speech input may be used to detect a possible alcoholic intoxication of the driver. For that matter a large part of the new Alcohol Language Corpus (ALC) edited by the Bavarian Archive of Speech Signals (BAS) will be used for a broad statistical investigation of possible feature candidates for classification. In this contribution we present the motivation and the design of the ALC corpus as well as first results from fundamental
frequency and rhythm analysis. Our analysis by comparing
sober and alcoholized speech of the same individuals suggests that there are in fact promising features that can automatically be derived from the speech signal during the speech recognition process and will indicate intoxication for most speakers
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