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Invariant-Based Online Software Anomaly Detection And Selective Regression Testing, Yizhen Chen
Invariant-Based Online Software Anomaly Detection And Selective Regression Testing, Yizhen Chen
Legacy Theses & Dissertations (2009 - 2024)
Software has been extensively used in various domains to provide online services. With the growing popularity of these types of applications, the quality of the software has a great impact on many of our daily activities [1]. Reliable software executions that deliver expected outcomes are essential for quality services. Software is considered abnormal when its behavior deviates from what is expected at any point during its execution. When anomalous behavior propagates to an exit point of the software and produces an incorrect output or an unexpected termination of the execution, it is considered a software failure. An anomaly may or …
Emotion Forecasting In Dyadic Conversation : Characterizing And Predicting Future Emotion With Audio-Visual Information Using Deep Learning, Sadat Shahriar
Emotion Forecasting In Dyadic Conversation : Characterizing And Predicting Future Emotion With Audio-Visual Information Using Deep Learning, Sadat Shahriar
Legacy Theses & Dissertations (2009 - 2024)
Emotion forecasting is the task of predicting the future emotion of a speaker, i.e., the emotion label of the future speaking turn–based on the speaker’s past and current audio-visual cues. Emotion forecasting systems require new problem formulations that differ from traditional emotion recognition systems. In this thesis, we first explore two types of forecasting windows(i.e., analysis windows for which the speaker’s emotion is being forecasted): utterance forecasting and time forecasting. Utterance forecasting is based on speaking turns and forecasts what the speaker’s emotion will be after one, two, or three speaking turns. Time forecasting forecasts what the speaker’s emotion will …