Speech-Emotion-Classification (ONNX)

Speech-Emotion-Classification

Speech-Emotion-Classification is a fine-tuned version of facebook/wav2vec2-base-960h for multi-class audio classification, specifically trained to detect emotions in speech. This model utilizes the Wav2Vec2ForSequenceClassification architecture to accurately classify speaker emotions from audio signals.

Intended Use

• Speech Emotion Analytics – Analyze speaker emotions in call centers, interviews, or therapeutic sessions.
• Conversational AI Personalization – Adjust voice assistant responses based on detected emotion.
• Mental Health Monitoring – Support emotion recognition in voice-based wellness or teletherapy apps.
• Voice Dataset Curation – Tag or filter speech datasets by emotion for research or model training.
• Media Annotation – Automatically annotate podcasts, audiobooks, or videos with speaker emotion metadata.