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SEGAA: A Unified Approach to Predicting Age, Gender, and Emotion in Speech
March 5, 2024, 2:43 p.m. | Aron R, Indra Sigicharla, Chirag Periwal, Mohanaprasad K, Nithya Darisini P S, Sourabh Tiwari, Shivani Arora
cs.LG updates on arXiv.org arxiv.org
Abstract: The interpretation of human voices holds importance across various applications. This study ventures into predicting age, gender, and emotion from vocal cues, a field with vast applications. Voice analysis tech advancements span domains, from improving customer interactions to enhancing healthcare and retail experiences. Discerning emotions aids mental health, while age and gender detection are vital in various contexts. Exploring deep learning models for these predictions involves comparing single, multi-output, and sequential models highlighted in this …
abstract age analysis applications arxiv cs.ai cs.cl cs.lg cs.sd customer customer interactions domains eess.as emotion gender healthcare human importance interactions interpretation retail speech study tech type vast voice voices
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