Data-driven models require high-fidelity data of sufficient quantity and granularity. This is
challenging in a complex chemical processing system due to frequent sensor breakdown …

Despite the recent progress in speech emotion recognition (SER), state-of-the-art systems
are unable to achieve improved performance in cross-language settings. In this paper, we …

Speech emotion recognition (SER) classifies emotions using low-level features or a
spectrogram of an utterance. When SER methods are trained and tested using different …

Due to the scarcity of high-quality labeled speech emotion data, it is natural to apply transfer
learning to emotion recognition. However, transfer learning-based speech emotion …

Speech plays an important role in human–computer emotional interaction. FaceNet used in
face recognition achieves great success due to its excellent feature extraction. In this study …

Speech emotion recognition systems have high computational requirements for deep
learning models and low generalizability mainly because of the poor reliability of emotional …

Abstract Speech Emotion Recognition (SER) performance degrades when their training and
test conditions or corpora differ. Cross-corpus SER (CCSER) is a research branch that …

Cross-corpus speech emotion recognition (SER) seeks to generalize the ability of inferring
speech emotion from a well-labeled corpus to an unlabeled one, which is a rather …

False information, such as rumours, has seriously affected our daily lives and threatened the
political, economic, cultural and other fields. Therefore, rumour detection on social media …

This work presents a hierarchical Bayesian network-based model for handling dynamic
nature, data variabilities, and information fusion in a dynamical process system. The overall …