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The performance of speech emotion classifiers greatly degrade when the training conditions do not match the testing conditions. This problem is observed in cross-corpora evaluations, even when the corpora are similar. The lack of generalization is particularly problematic when the emotion classifiers are used in real applications. This study addresses this problem by combining active learning (AL)...
Model-Based Testing (MBT) is a method for automating software testing and improving fault detection by using an abstracted model of the system under test to systematically generate and execute test cases. One of the main challenges in MBT is the efficient locating of fundamental causes of errors, which can be achieved using root cause analysis. As MBT is being applied to many diverse domains using...
Testing for security related issues is an important task of growing interest due to the vast amount of applications and services available over the internet. In practice testing for security often is performed manually with the consequences of higher costs, and no integration of security testing with today's agile software development processes. In order to bring security testing into practice, many...
This article describes the development of adaptive testing in response to the ever-growing need to dynamically and cost-effectively tailor IC testing to discriminately manage manufacturing process variations. Various degrees of adoption are presented, together with benefits and examples of its use. Finally, challenges for future development are discussed.
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