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Forensic Voice Comparison (FVC) is increasingly using the likelihood ratio (LR) in order to indicate whether the evidence supports the prosecution (same-speaker) or defender (different-speakers) hypotheses. Nevertheless, the LR accepts some practical limitations due both to its estimation process itself and to a lack of knowledge about the reliability of this (practical) estimation process. It is...
Automatic emotion recognition in realistic domains is a challenging task given the subtle expressive behaviors that occur during human interactions. The challenges start with noisy emotional descriptors provided by multiple evaluators, which are characterized by low interevaluator agreement. Studies have suggested that evaluators are more consistent in detecting qualitative relations between episodes...
Smart cities and smart homes are booming fields of development of pervasive systems. With the high stakes these systems have to manage, and their sheer complexity, anomalies have to be considered. In these complex systems are many connected components with computing capacities. They can manage anomalies, even if partially, and can act as some kind of expert systems. These expert systems can be relied...
It is becoming clear that one key characteristic of 5G communication systems will be heterogeneity. Heterogeneity is important to be able to reuse equipment that is available, extract maximum capacity from what is allowed to be used in given spectrum bands and locations due to regulatory limitations, and to match capabilities to the extremely wide range of use cases of 5G. Importantly, this heterogeneity...
We are interested in using purely network-based techniques to assist in matching instances across databases that can be represented as complex networks. In particular we are interested in the individuality of the influence neighbourhood of a node (the sub graph induced by its in-neighbours) in a directed network. We derive a paper citation network from the archived Cite Seer database and use this...
When it comes to analysis and interpretation of the results of subjective QoE studies, one often witnesses a lack of attention to the diversity in subjective user ratings. In extreme cases, solely Mean Opinion Scores (MOS) are reported, causing the loss of important information on the user rating diversity. In this paper, we emphasize the importance of considering the Standard deviation of Opinion...
In the product development process, test planning can be a time-consuming task, in particular, the test methods for product reliability are usually selected manually because many documents must be referred to when selecting suitable test methods. To make this process more efficient, we have been researched methods to support test planning. In this paper a new automatic selection method for test plans...
In this paper, we present an analysis of different approaches relative to the correction of belief functions based on the results given by a confusion matrix. Three different mechanisms based on discountings are detailed. These methods have the objective to assess the discounting rates to be assigned to a source of information. These discounting rates allow to correct raw data, based on learnt decisions...
We present Path Diversification, a new mechanism that can be used to select multiple paths between a given ingress and egress node pair using a quantified diversity measure to achieve maximum flow reliability. The path diversification mechanism is targeted at the end-to-end layer, but can be applied at any level for which a path discovery service is available, e.g. intra-realm routing or inter-realm...
Automatic inference of affect relies on representative data. For viable applications of such technology the use of naturalistic over posed data has been increasingly emphasised. Creating a repository of naturalistic data is however a massively challenging task. We report results from a data collection exercise in one of the most significant application areas of affective computing, namely computer-based...
In this paper, we describe a system for correcting English preposition errors automatically. Non-native English writers often make these errors. Our system uses rules extracted automatically based on preposition context features, such as preceding and following nouns. Additional rules are generated recursively from the extracted rules using inductive learning. Our system achieves 82% accuracy and...
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