Year: 2024
Type: article
Abstract: Speech emotion recognition (SER) is a burgeoning field in AI that analyzes vocal characteristics to understand human emotions. It delves deeper than the literal meaning of words, uncovering emotional cues hidden within speech patterns. Pitch, loudness, and speech rate are just a few features that vary with emotional state. SER utilizes machine learning algorithms to classify these features into categories like happiness, sadness, or anger. This technology offers a treasure trove of possibilities, from enhancing human-computer interaction to revolutionizing customer service and even aiding in mental health assessments. As SER continues to evolve, it holds the potential to transform how we connect with machines, fostering deeper understanding and richer emotional experiences.
DOI: 10.61808/jsrt95
Authors: Mr. Anandappa, Mrs. Kavita Mudnal
Institution: Government of Karnataka
Language: English
Topic: Emotion and Mood Recognition
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4395038787