Model-based approaches to handling additive noise in reverberant environments

Model-based approaches to handle additive and convolutional noise have been extensively investigated and used. However, the application of these schemes to handling reverberant noise has received less attention. This paper examines the extension of two standard additive/convolutional noise approaches to handling reverberant noise. The first is an extension of vector Taylor series (VTS) compensation, reverberant VTS, where a mismatch function including reverberant noise is used. The second scheme modifies constrained MLLR to allow a wide-span of frames to be taken into account and projected into the required dimensionality. To allow additive noise to be handled, both these schemes are combined with standard VTS. The approaches are evaluated and compared on two tasks, MC-WSJ-AV, and a reverberant simulated version of AURORA-4. © 2011 IEEE.

Effective handling of dialogue state in the hidden information state POMDP-based dialogue manager

Effective dialogue management is critically dependent on the information that is encoded in the dialogue state. In order to deploy reinforcement learning for policy optimization, dialogue must be modeled as a Markov Decision Process. This requires that the dialogue statemust encode all relevent information obtained during the dialogue prior to that state. This can be achieved by combining the user goal, the dialogue history, and the last user action to form the dialogue state. In addition, to gain robustness to input errors, dialogue must be modeled as a Partially Observable Markov Decision Process (POMDP) and hence, a distribution over all possible states must be maintained at every dialogue turn. This poses a potential computational limitation since there can be a very large number of dialogue states. The Hidden Information State model provides a principled way of ensuring tractability in a POMDP-based dialogue model. The key feature of this model is the grouping of user goals into partitions that are dynamically built during the dialogue. In this article, we extend this model further to incorporate the notion of complements. This allows for a more complex user goal to be represented, and it enables an effective pruning technique to be implemented that preserves the overall system performance within a limited computational resource more effectively than existing approaches. © 2011 ACM.

Handling uncertainty in housing stock models

Housing stock models can be useful tools in helping to assess the environmental and socio-economic impacts of retrofits to residential buildings; however, existing housing stock models are not able to quantify the uncertainties that arise in the modelling process from various sources, thus limiting the role that they can play in helping decision makers. This paper examines the different sources of uncertainty involved in housing stock models and proposes a framework for handling these uncertainties. This framework involves integrating probabilistic sensitivity analysis with a Bayesian calibration process in order to quantify uncertain parameters more accurately. The proposed framework is tested on a case study building, and suggestions are made on how to expand the framework for retrofit analysis at an urban-scale. © 2011 Elsevier Ltd.

A workbook-based methodology for implementing concurrent engineering

Concurrent Engineering demands a new way of working and many organisations experience difficulty during implementation. The research described in this paper has the aim to develop a paper-based workbook style methodology that companies can use to increase the benefits generated by Concurrent Engineering, while reducing implementation costs, risk and time. The three-stage methodology provides guidance based on knowledge accumulated from implementation experience and best practitioners. It encourages companies to learn to manage their Concurrent Engineering implementation by taking actions which expose them to new and valuable experiences. This helps to continuously improve understanding of how to maximise the benefits from Concurrent Engineering. The methodology is particularly designed to cater for organisational and contextual uniqueness, as Concurrent Engineering implementations will vary from company to company. Using key actions which improve the Concurrent Engineering implementation process, individual companies can develop their own 'best practice' for product development. The methodology ensures that key implementation issues, which are primarily human and organisational, are addressed using simple but proven techniques. This paper describes the key issues that the majority of companies face when implementing Concurrent Engineering. The structure of the methodology is described to show how the issues are addressed and resolved. The key actions used to improve the Concurrent Engineering implementation process are explained and their inclusion in the implementation methodology described. Relevance to industry. Implementation of Concurrent Engineering concepts in manufacturing industry has not been a straightforward process. This paper describes a workbook-style tool that manufacturing companies can use to accelerate and improve their Concurrent Engineering implementation. © 1995.