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.
432 stars. No commits in the last 6 months.
Use this if you need to automatically categorize the emotion conveyed in spoken words or singing from audio files.
Not ideal if you need to detect emotions from text, images, or real-time conversations, or if you require a very fine-grained analysis beyond the eight specified emotions.
Stars
432
Forks
141
Language
Python
License
GPL-3.0
Category
Last pushed
Jul 01, 2023
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