Speech Emotion Recognition (SER) is a growing field at the intersection of speech processing and affective computing. It enables machines to detect the emotional state of a speaker using vocal cues.

Speech Emotion Recognition (SER) is a significant area of research with diverse applications, including human-computer interaction, affective computing, and mental health monitoring.

Speech Emotion Recognition (SER) involves identifying and analyzing emotions conveyed through speech signals. It utilizes techniques from machine learning and signal processing to extract features ...

Recognizing the affective qualities of speech while ignoring its semantic content is the goal of Speech Emotion Recognition (SER). Automatically conducting this activity using programmed devices is ...