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arXiv Machine Learning By Nishargo Nigar

Speech Emotion Recognition Using CNN and Its Use Case in Digital Healthcare

Read the original on arXiv Machine Learning →

The paper presents a convolutional neural network (CNN) model for speech emotion recognition (SER), aiming to classify emotions from audio recordings. It evaluates the model using precision, recall, and F1 score, and explores how various input and output parameters influence performance. The study applies the SER system to digital healthcare, proposing it as a bridge between human emotional states and artificial intelligence.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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