Speech emotion recognition system with librosa
PA Babu, VS Nagaraju… - 2021 10th IEEE …, 2021 - ieeexplore.ieee.org
2021 10th IEEE international conference on communication systems …, 2021•ieeexplore.ieee.org
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 …
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 …
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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