Speech Emotion Recognition System With Librosa

P. Babu, V. Siva Nagaraju, Rajeev Ratna Vallabhuni
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引用次数: 6

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%.
基于Librosa的语音情感识别系统
在本文中,我们提出了一个系统,将分析语音信号,并从基于组合的相同有效的解决方案中收集情感。该系统仅使用深度学习和机器学习(ML)算法的概念识别信号或语音中存在的情绪。利用上述方法,系统将确定语音信号中存在的八种情绪;愤怒、悲伤、快乐、中性、冷静、恐惧、厌恶和惊讶。该系统是用python语言和librosa(声音文件库)构建的,它们是用于音频分析特定应用的更广泛的scikit库的一部分。该系统将从互联网上名为RAVDESS的数据集中接收声音文件。然后,它将分析WAV格式的音频文件的频谱图,并将系统的效率返回给我们,这是预期的结果。我们的效率达到了81.82%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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