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STRESS AND ANXIETY DETECTION THROUGH SPEECH RECOGNITION USING DEEP NEURAL NETWORK

  • Unique Paper ID: 154638
  • Volume: 8
  • Issue: 11
  • PageNo: 730-734
  • Abstract:
  • Stress is a feeling of emotional tension. It can have an influence on our mental health and for the people around us. While anxiety is a natural reaction to stress which can be fearful this can lead to panic attacks. These mental issues have to be addressed by everyone. This paper explains how we are using vocal/audio dataset to detect stress and anxiety in a person. We have developed a stress and anxiety detection model using deep neural network. Here audio datasets is considered from Kaggle in which the audio consists of 7 emotions i.e., joy, fear, disgust, neutral, sadness, surprised and anger. These audio datasets are used to train and test classification models like CNN. Then the audio is pre-processed through acoustic feature extraction, classified through CNN which provides the accuracy based on those 7 emotions. By this we can predict if the person is stressed or has anxiety
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 8
  • Issue: 11
  • PageNo: 730-734

STRESS AND ANXIETY DETECTION THROUGH SPEECH RECOGNITION USING DEEP NEURAL NETWORK

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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