Artificial Intelligence Based Emotion Identification Using Analog Waves

Authors

  • PIN-YU HUANG Dept. of Electrical Engineering, National Taiwan University of Science and Technology (Taiwan Tech) Taipei, Taiwan, R. O. C
  • PEI-HSUAN YANG Dept. of Electrical Engineering, National Taiwan University of Science and Technology (Taiwan Tech) Taipei, Taiwan, R. O. C
  • SHIH-YIN HUANG Dept. of Electrical Engineering, National Taiwan University of Science and Technology (Taiwan Tech) Taipei, Taiwan, R. O. C
  • YUE-NUO YAN Dept. of Electrical Engineering, National Taiwan University of Science and Technology (Taiwan Tech) Taipei, Taiwan, R. O. C

Keywords:

Librosa, SciKit, Sound File, Spectrogram

Abstract

In this paper, we propose a system that will analyze the speech signals and gather the emotion from the same efficient solution based on combinations. This system solely served to identify emotions present in the signal or speech using concepts of deep learning and algorithms of machine learning (ML). Using the above mentioned, the system will determine the eight emotions present in the speech signal; anger, sad, happy, neutral, calm, fearful, disgust and surprised. The system is built with the language python and librosa, sound file libraries, which are part of the more extensive scikit library used for specific applications of audio analysis. The system will receive the sound files from the dataset present on the internet called RAVDESS. It will then analyze the audio files' spectrograms in WAV format and return us the efficiency of the system, which is the intended Outcome. We have achieved an efficiency rate of 81.82%.

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Published

2023-05-20

How to Cite

HUANG, P.-Y., YANG, P.-H., HUANG, S.-Y., & YAN, Y.-N. (2023). Artificial Intelligence Based Emotion Identification Using Analog Waves. International Journal of Communication and Computer Technologies, 11(1), 68–74. Retrieved from https://ijccts.org/index.php/pub/article/view/173

Issue

Section

Research Article