Audio spectrogram analysis in IoT paradigm for the classification of psychological-emotional characteristics

• Published in: International journal of information technology (Singapore. Online) Vol. 17; no. 6; pp. 3539 - 3549
• Main Authors: Kumar, Ankit, Singh, Sushil Kumar, Bhardwaj, Indu, Singh, Prakash Kumar, Khanna, Ashish, Brahma, Biswajit
• Format: Journal Article
• Language: English
• Published: Singapore Springer Nature Singapore 01.07.2025; Springer Nature B.V
• Subjects: Artificial Intelligence; Artificial neural networks; Classification; Computer Imaging; Computer Science; Computer vision; Emotions; Generative adversarial networks; Human behavior; Image Processing and Computer Vision; Internet of Things; Interrogation; Machine Learning; Microphones; Original Research; Pattern Recognition and Graphics; Software Engineering; Vision; Zero crossing rate (ZCR); Emotion recognition; Audio spectrogram; Mel-frequency cepstral coefficient (MFCC); Generative adversarial networks (GAN); Convolutional neural network (CNN); Harmonic to noise rate (HNR)

Psychological activities have various dimensions in which they correlate with their respective behavior generated by the human body. Understanding the relationship of psychological events from external action units is one of the research subjects to explore various human behavior and their dependenc...