Cross-Lingual spoken language understanding from unaligned data using discriminative classification models and machine translation

This paper investigates several approaches to bootstrapping a new spoken language understanding (SLU) component in a target language given a large dataset of semantically-annotated utterances in some other source language. The aim is to reduce the cost associated with porting a spoken dialogue system from one language to another by minimising the amount of data required in the target language. Since word-level semantic annotations are costly, Semantic Tuple Classifiers (STCs) are used in conjunction with statistical machine translation models both of which are trained from unaligned data to further reduce development time. The paper presents experiments in which a French SLU component in the tourist information domain is bootstrapped from English data. Results show that training STCs on automatically translated data produced the best performance for predicting the utterance's dialogue act type, however individual slot/value pairs are best predicted by training STCs on the source language and using them to decode translated utterances. © 2010 ISCA.

COMPRESSOR BLADE

A blade (2) for a compressor comprising a pressure surface (6) and a suction surface (4), wherein the suction surface (4) comprises: a discontinuity in the chord-wise curvature of an intermediate portion of the suction surface between the blade leading edge and blade trailing edge; and a slot (20) arranged along at least a portion of the blade (2) in a substantially span-wise direction, the slot (2) being disposed at or near the said change in curvature, such that when in use lower momentum fluid near the suction surface (4) is aspirated into the slot (20).

Evaluation of Setup Procedures on Mobile Devices Based on Users’ Initial Experience

Users’ initial perceptions of their competence are key motivational factors for further use. However, initial tasks on a mobile operating system (OS) require setup procedures, which are currently largely inconsistent, do not provide users with clear, visible and immediate feedback on their actions, and require significant adjustment time for first-time users. This paper reports on a study with ten users, carried out to better understand how both prior experience and initial interaction with two touchscreen mobile interfaces (Apple iOS and Google Android) affected setup task performance and motivation. The results show that the reactions to setup on mobile interfaces appear to be partially dependent on which device was experienced first. Initial experience with lower-complexity devices improves performance on higher-complexity devices, but not vice versa. Based on these results, the paper proposes six guidelines for designers to design more intuitive and motivating user interfaces (UI) for setup procedures. The preliminary results indicate that these guidelines can contribute to the design of more inclusive mobile platforms and further work to validate these findings is proposed.

Variability in encoding precision accounts for visual short-term memory limitations.

It is commonly believed that visual short-term memory (VSTM) consists of a fixed number of "slots" in which items can be stored. An alternative theory in which memory resource is a continuous quantity distributed over all items seems to be refuted by the appearance of guessing in human responses. Here, we introduce a model in which resource is not only continuous but also variable across items and trials, causing random fluctuations in encoding precision. We tested this model against previous models using two VSTM paradigms and two feature dimensions. Our model accurately accounts for all aspects of the data, including apparent guessing, and outperforms slot models in formal model comparison. At the neural level, variability in precision might correspond to variability in neural population gain and doubly stochastic stimulus representation. Our results suggest that VSTM resource is continuous and variable rather than discrete and fixed and might explain why subjective experience of VSTM is not all or none.

New approaches for enhancing light emission from Er-based materials and devices

In this work, we present some approaches recently developed for enhancing light emission from Er-based materials and devices. We have investigated the luminescence quenching processes limiting quantum efficiency in light-emitting devices based on Si nanoclusters (Si nc) or Er-doped Si nc. It is found that carrier injection, while needed to excite Si nc or Er ions through electron-hole recombination, at the same time produces an efficient non-radiative Auger de-excitation with trapped carriers. A strong light confinement and enhancement of Er emission at 1.54 μm in planar silicon-on-insulator waveguides containing a thin layer (slot) of SiO2 with Er-doped Si nc at the center of the Si core has been obtained. By measuring the guided photoluminescence from the cleaved edge of the sample, we have observed a more than fivefold enhancement of emission for the transverse magnetic mode over the transverse electric one at room temperature. Slot waveguides have also been integrated with a photonic crystal (PhC), consisting of a triangular lattice of holes. An enhancement by more than two orders of magnitude of the Er near-normal emission is observed when the transition is in resonance with an appropriate mode of the PhC slab. Finally, in order to increase the concentration of excitable Er ions, a completely different approach, based on Er disilicate thin films, has been explored. Under proper annealing conditions crystalline and chemically stable Er2Si2O7 films are obtained; these films exhibit a strong luminescence at 1.54 μm owing to the efficient reduction of the defect density. © 2008 Elsevier B.V. All rights reserved.

THE SENSITIVITY OF 2D COMPRESSOR INCIDENCE RANGE TO IN-SERVICE GEOMETRIC VARIATION

The loss mechanisms which control 2D incidence range are discussed with an emphasis on determining which real in-service geometric variations will have the largest impact. For the majority of engine compressor blades (Minlet>0.55) both the negative and positive incidence limits are controlled by supersonic patches. It is shown that these patches are highly sensitive to the geometric variations close to, and around the leading edge. The variations used in this study were measured from newly manufactured as well as ex-service blades. Over most the high pressure compressor considered, it was shown that manufacture variations dominated. The first part of the paper shows that, despite large geometric variations (~10% of leading edge thickness), the incidence range responded in a linear way. The result of this is that the geometric variations have little effect on the mean incidence range of a row of blades. In the second part of the paper a region of the design space is identified where non-linear behavior can result in a 10% reduction in positive incidence range. The mechanism for this is reported and design guidelines for its avoidance offered. In the final part of the paper, the linear behavior at negative incidence and the transonic nature of the flow is exploited to design a robust asymmetric leading edge with a 5% increase in incidence range.

Cortical substrates for exploratory decisions in humans.

Decision making in an uncertain environment poses a conflict between the opposing demands of gathering and exploiting information. In a classic illustration of this 'exploration-exploitation' dilemma, a gambler choosing between multiple slot machines balances the desire to select what seems, on the basis of accumulated experience, the richest option, against the desire to choose a less familiar option that might turn out more advantageous (and thereby provide information for improving future decisions). Far from representing idle curiosity, such exploration is often critical for organisms to discover how best to harvest resources such as food and water. In appetitive choice, substantial experimental evidence, underpinned by computational reinforcement learning (RL) theory, indicates that a dopaminergic, striatal and medial prefrontal network mediates learning to exploit. In contrast, although exploration has been well studied from both theoretical and ethological perspectives, its neural substrates are much less clear. Here we show, in a gambling task, that human subjects' choices can be characterized by a computationally well-regarded strategy for addressing the explore/exploit dilemma. Furthermore, using this characterization to classify decisions as exploratory or exploitative, we employ functional magnetic resonance imaging to show that the frontopolar cortex and intraparietal sulcus are preferentially active during exploratory decisions. In contrast, regions of striatum and ventromedial prefrontal cortex exhibit activity characteristic of an involvement in value-based exploitative decision making. The results suggest a model of action selection under uncertainty that involves switching between exploratory and exploitative behavioural modes, and provide a computationally precise characterization of the contribution of key decision-related brain systems to each of these functions.