Phone-level pronunciation scoring and assessment for interactive language learning

This paper investigates a method of automatic pronunciation scoring for use in computer-assisted language learning (CALL) systems. The method utilizes a likelihood-based `Goodness of Pronunciation' (GOP) measure which is extended to include individual thresholds for each phone based on both averaged native confidence scores and on rejection statistics provided by human judges. Further improvements are obtained by incorporating models of the subject's native language and by augmenting the recognition networks to include expected pronunciation errors. The various GOP measures are assessed using a specially recorded database of non-native speakers which has been annotated to mark phone-level pronunciation errors. Since pronunciation assessment is highly subjective, a set of four performance measures has been designed, each of them measuring different aspects of how well computer-derived phone-level scores agree with human scores. These performance measures are used to cross-validate the reference annotations and to assess the basic GOP algorithm and its refinements. The experimental results suggest that a likelihood-based pronunciation scoring metric can achieve usable performance, especially after applying the various enhancements.

An experimental model of relay deployment planning tool for a wireless sensor network system to monitor civil engineering structures

It is essential to monitor deteriorated civil engineering structures cautiously to detect symptoms of their serious disruptions. A wireless sensor network can be an effective system for monitoring civil engineering structures. It is fast to deploy sensors especially in difficult-to-access areas, and it is extendable without any cable extensions. Since our target is to monitor deteriorations of civil engineering structures such as cracks at tunnel linings, most of the locations of sensors are known, and sensors are not required to move dynamically. Therefore, we focus on developing a deployment plan of a static network in order to reduce the value of a cost function such as initial installation cost and summation of communication distances of the network. The key issue of the deployment is the location of relays that forward sensing data from sensors to a data collection device called a gateway. In this paper, we propose a relay deployment-planning tool that can be used to design a wireless sensor network for monitoring civil engineering structures. For the planning tool, we formalize the model and implement a local search based algorithm to find a quasi-optimal solution. Our solution guarantees two routings from a sensor to a gateway, which can provide higher reliability of the network. We also show the application of our experimental tool to the actual environment in the London Underground.

Cure processing modeling and cure cycle simulation of epoxy-terminated poly(phenylene ether ketone) .3. Determination of the time of pressure application

The curing temperature, pressure, and curing time have significant influence on finished thermosetting composite products. The time of pressure application is one of the most important processing parameters in the manufacture of a thermosetting composite. The determination of the time of pressure application relies on analysis of the viscosity variation of the polymer, associated with curing temperature and curing time. To determine it, the influence of the time of pressure application on the physical properties of epoxy-terminated poly(phenylene ether ketone) (E-PEK)-based continuous carbon fiber composite was studied. It was found that a stepwise temperature cure cycle is more suitable for manufacture of this composite. There are two viscosity valleys, in the case of the E-PEK system, associated with temperature during a stepwise cure cycle. The analysis on the effects of reinforcement fraction and defect content on the composite sheet quality indicates that the width-adjustable second viscosity valley provides a suitable pressing window. The viscosity, ranging from 400 to 1200 Pa . s at the second viscosity valley, is the optimal viscosity range for applying pressure to ensure appropriate resin flow during curing process, which enables one to get a finished composite with optimal fiber volume fraction and low void content. (C) 1997 John Wiley & Sons, Inc.

Performance evaluation of the RPL Protocol in fixed and mobile sinks low-power and lossy networks.

Low-Power and Lossy-Network (LLN) are usually composed of static nodes, but the increase demand for mobility in mobile robotic and dynamic environment raises the question how a routing protocol for low-power and lossy-networks such as (RPL) would perform if a mobile sink is deployed. In this paper we investigate and evaluate the behaviour of the RPL protocol in fixed and mobile sink environments with respect to different network metrics such as latency, packet delivery ratio (PDR) and energy consumption. Extensive simulation using instant Contiki simulator show significant performance differences between fixed and mobile sink environments. Fixed sink LLNs performed better in terms of average power consumption, latency and packet delivery ratio. The results demonstrated also that RPL protocol is sensitive to mobility and it increases the number of isolated nodes.

Adaptation of Dopamine Neurons' Mismatch Sensitivity Is not Compatible With Reinforcement Learning Theory

Recent electrophysical data inspired the claim that dopaminergic neurons adapt their mismatch sensitivities to reflect variances of expected rewards. This contradicts reward prediction error theory and most basal ganglia models. Application of learning principles points to a testable alternative interpretation-of the same data-that is compatible with existing theory.