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Automated Speech Recognition System to Detect Babies’ Feelings through Feature Analysis

Computers, Materials & Continua 2022年第11期73卷 4349-4367页

作者： Sana Yasin Umar Draz Tariq Ali Kashaf Shahid Amna Abid rukhsana bibi Muhammad Irfan Mohammed A.Huneif Sultan A.Almedhesh Seham M.Alqahtani Alqahtani Abdulwahab Mohammed Jamaan Alzahrani Dhafer Batti Alshehri Alshehri Ali Abdullah Saifur Rahman Faculty of Computing University of OkaraOkara57000Pakistan Department of Computer Science University of SahiwalSahiwal57000PunjabPakistan Computer Science Department COMSATS University IslamabadLahore Campus57000Pakistan Department of Computer Science CUISahiwal CampusSahiwal57000Pakistan Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Pediatric Department Medical CollegeNajran University Saudi ArabiaNajran61441Saudi Arabia Consultant of ORL&HNs and Facial Plastic Surgery College of MedicineNajran University Saudi ArabiaNajran61441Saudi Arabia

Diagnosing a baby’s feelings poses a challenge for both doctors and parents because babies cannot explain their feelings through expression or *** the emotions of babies and their associated expressions during different sensations such as hunger,pain,etc.,is a complicated *** infancy,all communication and feelings are propagated through cryspeech,which is a natural *** clinical methods can be used to diagnose a baby’s diseases,but nonclinical methods of diagnosing a baby’s feelings are *** such,in this study,we aimed to identify babies’feelings and emotions through their cry using a nonclinical *** in the cry sound can be identified using our method and used to assess the baby’s *** considered the frequency of the cries from the energy of the *** feelings represented by the infant’s cry are judged to represent certain sensations expressed by the child using the optimal frequency of the recognition of a real-world audio *** used machine learning and artificial intelligence to distinguish cry tones in real time through feature *** experimental group consisted of 50%each male and female babies,and we determined the relevancy of the results against different *** application produced real-time results after recognizing a child’s cry *** novelty of our work is that we,for the first time,successfully derived the feelings of young children through the cry-speech of the child,showing promise for end-user applications.

关键词： Cry-to-speak machine learning artificial intelligence cry speech detection babies

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