Domestic cats are close friend of human from the era of human civilization. Cat can produce variety of sounds according to moods or situations. The automatic vocal sounds classification is important for better understand our close friend's demands or requirements based one the sound categorization. In this book we illustrate some deep learning-based techniques to classify the domestic cat sound based on its moods. We collect the data samples, use deep neural networks (supervised and unsupervised) to classify the sounds and then analysis them over various parameters.
Yagya Raj Pandeya
Mr. Pandeya is a Ph.D. fellow at Chonbuk National University, Korea. His research interests include video and audio processing, computer vision, emotion engineering etc. He has three years of academic and two years of employment experience. He machines learning and artificial intelligence expert with three years of professional work experience.
Number of Pages:
LAP LAMBERT Academic Publishing
Cat sound classification, Cat sound dataset, Neural Network features, Feature visualization
SCIENCE / Ecology