Speech Emotion Recognition System With Librosa

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...

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Bibliographic Details
Published in2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT) pp. 421 - 424
Main Authors Babu, P. Ashok, Siva Nagaraju, V., Vallabhuni, Rajeev Ratna
Format Conference Proceeding
LanguageEnglish
Published IEEE 18.06.2021
Subjects
Communication systems
Conferences
Deep learning
Emotion recognition
Knowledge engineering
Librosa
Machine learning algorithms
SciKit
Sound File
Spectrogram
Visualization
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Summary: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%.
DOI:10.1109/CSNT51715.2021.9509714