Survey of Affect Representation Schemes used in Automatic Affect Prediction for Speech Emotion Recognition: A Systematic Review

Automatic affect prediction systems usually assume its underlying affect representation scheme (ARS). This systematic review aims to explore how different ARS are used for in affect prediction systems based on spoken input. The focus is only on the audio input from speakers. Various datasets for speech emotion recognition were also involved in...

Survey of Affect Representation Schemes used in Vision-Based Automatic Affect Prediction: A Systematic Literature Review

In human-human interactions, the majority of information is conveyed through body language, specifically facial expressions. Consequently, researchers have been interested in improving human-computer interactions through developing systems with automatic understanding of body language and facial expressions.  This technology is especially useful...

Investigating the performance of SPEA-II on automatic test case generation

Software testing is an important but time-consuming task, making automatic test case generation an appealing solution. The current state-of-the-art algorithm for test case generation is DynaMOSA, which is an improvement of NSGA-II that applies domain knowledge to make it more suitable for test case generation. Although these enhancements are...

Automatically Generating User-specific Recovery Procedures after Malware Infections

Malware poses a serious security risk in today’s digital environment. The defense against malware mainly relies on proactive detection. However, antivirus products often fail to detect new malware when the signature is not yet available. In the event of a malware infection, the common remediation strategy is reinstalling the system. However, the...

Mitigating Regional Accent Bias in ASR Systems

End-to-end Automatic Speech Recognition (ASR) systems improved drastically in recent years and they work extremely well on many large datasets. However, research shows that these models failed to capture the variability in speech production and have biases against the variant caused by the regional accented speech. Moreover, ASR research on...

Automatic segmentation of the spinal joints and intervertebral disks on low-dose computed tomography: an atlas-based approach

Introduction: Spondyloarthritis (SpA) belongs to the chronic inflammatory rheumatic diseases, and primarily affects the axial skeleton. Quantitative 18F-NaF PET/CT is a new imaging approach that shows promise for accurate diagnosis and treatment assessment. Manual segmentation of low-dose computed tomography (LDCT) for quantitative feature...

Automatic Speech Recognition for Air Traffic Control Using Open Data

Air Traffic Control (ATC) is tasked with ensuring safe separation between aircraft in a given Controlled Traffic Region (CTR). To achieve this an Air Traffic Controller (ATCo) verbally gives clearances using over the air communication. These clearances are kept track of by the ATCo using so-called ‘flight-strips’, which in modern systems are...

Improving whispered speech recognition using pseudo-whispered based data augmentation

Whispering, characterized by its soft, breathy, and hushed qualities, serves as a distinct form of speech commonly employed for private communication and can also occur in cases of pathological speech. The acoustic characteristics of whispered speech differ substantially from normally phonated speech and the scarcity of adequate training data...

Deep Learning-Based Automatic Detection and Classification of Rib Fractures from CT scans

Introduction: Trauma-induced rib fractures are a common injury, affecting millions of individuals globally each year. Although anteroposterior thoracic radiographs are part of the standard posttraumatic screening, the most sensitive modality, and therefore golden standard for diagnosing rib fractures, is computed tomography (CT). Still, between...

Applying Large-Scale Weakly Supervised Automatic Speech Recognition to Air Traffic Control

The application of automatic speech recognition in the air traffic control domain has been researched extensively. However, its primary application remains in the training and simulation of air traffic controllers. This is due to the insufficient performance of automatic speech recognition in specific environments, such as air traffic control,...