Automatic speech emotion recognition (SER) is a challenging component of human-
computer interaction (HCI). Existing literatures mainly focus on evaluating the SER …

In this letter, we propose a novel deep domain-adaptive convolutional neural network
(DDACNN) model to handle the challenging cross-corpus speech emotion recognition …

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 …

Speech Emotion Recognition (SER) plays a crucial role in applications involving human-
machine interaction. However, the scarcity of suitable emotional speech datasets presents a …

In this paper, we focus on the research of cross-corpus speech emotion recognition (SER),
in which the training (source) and testing (target) speech samples come from different …

Speech Emotion Recognition (SER) has become a growing focus of research in human-
computer interaction. An essential challenge in SER is to extract common attributes from …

Cross-corpus speech emotion recognition can be a useful transfer learning technique to
build a robust speech emotion recognition system by leveraging information from various …

Background One of the most critical issues in human-computer interaction applications is
recognizing human emotions based on speech. In recent years, the challenging problem of …

Domain generalization is a major challenge for cross-corpus speech emotion recognition.
The recognition performance built on" seen" source corpora is inevitably degraded when the …

Speech Emotion Recognition (SER) is a task related to many applications in the framework
of human-machine interaction. However, the lack of suitable speech emotional datasets …