Sentiment analysis is an important natural language processing issue that has many
applications in various fields. The increasing popularity of social networks and growth and …

Abstract Automatic Speech Emotion Recognition (ASER) has recently garnered attention
across various fields including artificial intelligence, pattern recognition, and human …

Conversational emotion recognition is a crucial research topic in human-computer
interactions. Due to the heavy annotation cost and inevitable label ambiguity, collecting …

While colonization has sociohistorically impacted people's identities across various
dimensions, those colonial values and biases continue to be perpetuated by sociotechnical …

Speech emotion recognition (SER) is essential for understanding a speaker's intention.
Recently, some groups have attempted to improve SER performance using a bidirectional …

Emotion recognition in conversations is challenging due to the multi-modal nature of the
emotion expression. We propose a hierarchical cross-attention model (HCAM) approach to …

Emotion recognition remains a complex task due to speaker variations and low-resource
training samples. To address these difficulties, we focus on the domain adversarial neural …

Approaches toward ordinal speech emotion recognition (SER) tasks are commonly based
on the categorical classification algorithms, where the rank-order emotions are arbitrarily …

This paper proposes a robust model for domain recognition of acoustic communication by
using Bidirectional LSTM and deep neural network. The proposed model consists of five …

Emotion recognition in conversations (ERC) has been challenging due to the dynamics and
complexity of emotions in conversations. Most current emotion recognition studies have …