Speech emotion recognition (SER) plays a vital role in improving the interactions between
humans and machines by inferring human emotion and affective states from speech signals …

Speech emotion recognition (SER) is a crucial field of research in artificial intelligence and
human–computer interaction. Extracting effective speech features for emotion recognition is …

Previous multilingual text-to-speech (TTS) approaches have considered leveraging
monolingual speaker data to enable cross-lingual speech synthesis. However, such data …

Speech emotion recognition (SER) plays a pivotal role in enhancing Human-computer
interaction (HCI) systems. This paper introduces a groundbreaking Capsule-enhanced …

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 …

Speech emotion recognition poses challenges due to the varied expression of emotions
through intonation and speech rate. In order to reduce the loss of emotional information …

Deterioration in the quality of a person's voice and speech is an early sign of Parkinson's
disease (PD). Although a number of computer‐based methods have been invested to use …

Speech emotion recognition has lots of applications such as human‐computer interaction
and health management. The current methods are challenged with the problems of fuzzy …

Experimental design allows us to more accurately determine the causal relationship
between variables correlated over time as compared to observational design based on …

Speech emotion recognition (SER) has garnered increasing attention due to its wide range
of applications in various fields, including human-machine interaction, virtual assistants, and …