Renovamen/Speech-Emotion-Recognition

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1314 stars · 230 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python library implementing speech emotion recognition with Keras/TensorFlow 2 using LSTM, CNN, SVM, and MLP models. It extracts audio features via librosa or OpenSMILE and achieves roughly 80% accuracy on standard emotion datasets.

Use cases

• classify emotions in audio recordings
• train a speech emotion recognition model
• extract features from speech audio with librosa or opensmile
• recognize emotion from wav files
• benchmark emotion recognition on RAVDESS or EMO-DB
• learn how to build audio classification models in Keras

When to choose

• you need a ready-made speech emotion recognition pipeline in Python
• you want to compare LSTM, CNN, SVM, and MLP on emotion classification
• you are working with RAVDESS, SAVEE, EMO-DB, or CASIA datasets

When to avoid

• you need real-time or production-scale emotion recognition
• you need pretrained models for languages or datasets not covered here
• you need a maintained actively developed project

Facets

library · maturity maintenance

machine-learning audio-processing speech-recognition deep-learning machine-learning speech-processing python cross-platform speech-emotion-recognition keras lstm cnn svm mlp librosa opensmile audio-classification audio natural-language-processing

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