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In automatic speech recognition (ASR), error correction after the initial search stage is a commonly used technique to improve performance. Whilst completely automatic error correction, such as full second pass rescoring using complex language models, is widely used, directed error correction, where the error locations are manually given, is of great interest in many scenarios. Previous works on directed...
Coverage model is the main technique to evaluate the thoroughness of dynamic verification of a Design-under-Verification (DUV). However, rather than achieving a high coverage, the essential purpose of verification is to expose as many bugs as possible. In this paper, we propose a novel verification methodology that leverages the early bug prediction of a DUV to guide and assess related verification...
Small sample size is often a limitation in reliability field tests for expensive, destructive systems, which makes it difficult to evaluate system reliability accurately. A new system's development process is usually comprised of several stages within which the system experiences design updating, and prototype field testing, thus enabling the improvement of system reliability. A dynamic Bayesian evaluation...
We present a novel general framework for distributed anomaly detection. In the framework, normal behavior is first learned from data from individual data sites using standard anomaly detection algorithms and then these models are combined when predicting anomalies from a new data set. We have investigated seven semi-supervised anomaly detection algorithms for learning normal behavior, as well as proposed...
Telecom churn prediction is one of the key factors which closely related to the development of telecommunications business. To solve the data imbalance problem exiting in this field, traditional researches always redistribute samples according to misclassification cost. But exiting researches in this area neither gave out the quantitative description of the misclassification cost nor set up a unified...
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