Speech-Emotion-Analyzer and emotion-classification-from-audio-files
About Speech-Emotion-Analyzer
MiteshPuthran/Speech-Emotion-Analyzer
The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)
This project helps businesses understand customer sentiment during calls or interactions. It takes audio speech as input and tells you if the speaker (male or female) is angry, calm, fearful, happy, or sad. Call center managers, marketers, or even product developers could use this to gauge emotional responses.
About emotion-classification-from-audio-files
marcogdepinto/emotion-classification-from-audio-files
Understanding emotions from audio files using neural networks and multiple datasets.
This project helps you understand the emotions expressed in human speech and song by analyzing audio files. It takes an audio recording as input and outputs a classification of the speaker's emotion from a list of eight categories: neutral, calm, happy, sad, angry, fearful, disgust, or surprised. This tool is ideal for researchers, behavioral analysts, or anyone needing to automatically identify emotional states from vocal recordings.
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