| library_name: transformers.js | |
| base_model: | |
| - prithivMLmods/Speech-Emotion-Classification | |
| # Speech-Emotion-Classification (ONNX) | |
| This is an ONNX version of [prithivMLmods/Speech-Emotion-Classification](https://huggingface.co/prithivMLmods/Speech-Emotion-Classification). It was automatically converted and uploaded using [this space](https://huggingface.co/spaces/onnx-community/convert-to-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-Classification` is designed for: | |
| * **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. |