630 research outputs found
Individual and Domain Adaptation in Sentence Planning for Dialogue
One of the biggest challenges in the development and deployment of spoken
dialogue systems is the design of the spoken language generation module. This
challenge arises from the need for the generator to adapt to many features of
the dialogue domain, user population, and dialogue context. A promising
approach is trainable generation, which uses general-purpose linguistic
knowledge that is automatically adapted to the features of interest, such as
the application domain, individual user, or user group. In this paper we
present and evaluate a trainable sentence planner for providing restaurant
information in the MATCH dialogue system. We show that trainable sentence
planning can produce complex information presentations whose quality is
comparable to the output of a template-based generator tuned to this domain. We
also show that our method easily supports adapting the sentence planner to
individuals, and that the individualized sentence planners generally perform
better than models trained and tested on a population of individuals. Previous
work has documented and utilized individual preferences for content selection,
but to our knowledge, these results provide the first demonstration of
individual preferences for sentence planning operations, affecting the content
order, discourse structure and sentence structure of system responses. Finally,
we evaluate the contribution of different feature sets, and show that, in our
application, n-gram features often do as well as features based on higher-level
linguistic representations
exploding clusters dynamics probed by XUV fluorescence
Clusters excited by intense laser pulses are a unique source of warm dense
matter, that has been the subject of intensive experimental studies. The
majority of those investigations concerns atomic clusters, whereas the
evolution of molecular clusters excited by intense laser pulses is less
explored. In this work we trace the dynamics of clusters
triggered by a few-cycle 1.45-m driving pulse through the detection of XUV
fluorescence induced by a delayed 800-nm ignition pulse. Striking differences
among fluorescence dynamics from different ionic species are observed
Model–data comparison and data assimilation of mid-Holocene Arctic sea ice concentration
The consistency between new quantitative reconstructions of Arctic sea ice
concentration based on dinocyst assemblages and the results of climate models
has been investigated for the mid-Holocene. The response of the models
mainly follows the increase in summer insolation, modulated to a limited
extent by changes in atmospheric circulation. This leads to differences
between regions in the models that are smaller than in the reconstruction. It
is, however, impossible to precisely assess the models' skills because the
sea ice concentration changes at the mid-Holocene are small in both the
reconstructions and the models and of the same order of magnitude as the
reconstruction uncertainty. Performing simulations with data assimilation
using the model LOVECLIM amplifies the regional differences and improves the
model–data agreement as expected. This is mainly achieved through a
reduction of the southward winds in the Barents Sea and an increase in the
westerly winds in the Canadian Basin, inducing an increase in the ice
concentration in the Barents and Chukchi seas. This underlines the potential
role of atmospheric circulation in explaining the reconstructed changes
during the Holocene
Services within a busy period of an M/M/1 queue and Dyck paths
We analyze the service times of customers in a stable M/M/1 queue in
equilibrium depending on their position in a busy period. We give the law of
the service of a customer at the beginning, at the end, or in the middle of the
busy period. It enables as a by-product to prove that the process of instants
of beginning of services is not Poisson. We then proceed to a more precise
analysis. We consider a family of polynomial generating series associated with
Dyck paths of length 2n and we show that they provide the correlation function
of the successive services in a busy period with (n+1) customers
Sum of exit times in series of metastable states in probabilistic cellular automata
Reversible Probabilistic Cellular Automata are a special class
of automata whose stationary behavior is described by Gibbs--like
measures. For those models the dynamics can be trapped for a very
long time in states which are very different from the ones typical
of stationarity.
This phenomenon can be recasted in the framework of metastability
theory which is typical of Statistical Mechanics.
In this paper we consider a model presenting two not degenerate in
energy
metastable states which form a series, in the sense that,
when the dynamics is started at one of them, before reaching
stationarity, the system must necessarily visit the second one.
We discuss a rule for combining the exit times
from each of the metastable states
The direct evaluation of attosecond chirp from a streaking measurement
We derive an analytical expression, from classical electron trajectories in a
laser field, that relates the breadth of a streaked photoelectron spectrum to
the group-delay dispersion of an isolated attosecond pulse. Based on this
analytical expression, we introduce a simple, efficient and robust procedure to
instantly extract the attosecond pulse's chirp from the streaking measurement.Comment: 4 figure
Deep Impression: Audiovisual Deep Residual Networks for Multimodal Apparent Personality Trait Recognition
Here, we develop an audiovisual deep residual network for multimodal apparent
personality trait recognition. The network is trained end-to-end for predicting
the Big Five personality traits of people from their videos. That is, the
network does not require any feature engineering or visual analysis such as
face detection, face landmark alignment or facial expression recognition.
Recently, the network won the third place in the ChaLearn First Impressions
Challenge with a test accuracy of 0.9109
Acoustic-prosodic automatic personality trait assessment for adults and children
This paper investigates the use of heterogeneous speech corpora for automatic assessment of personality traits in terms of the BigFive OCEAN dimensions. The motivation for this work is twofold: the need to develop methods to overcome the lack of children’s speech corpora, particularly severe when targeting personality traits, and the interest on cross-age comparisons of acoustic-prosodic features to build robust paralinguistic detectors. For this purpose, we devise an experimental setup with age mismatch utilizing the Interspeech 2012 Personality Subchallenge, containing adult speech, as training data. As test data, we use a corpus of children’s European Portuguese speech. We investigate various features sets such as the Sub-challenge baseline features, the recently introduced eGeMAPS features and our own knowledge-based features. The preliminary results bring insights into cross-age and -language detection of personality traits in spontaneous speech, pointing out to a stable set of acoustic-prosodic features for Extraversion and Agreeableness in both adult and child speech.info:eu-repo/semantics/publishedVersio
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