Guides

emotion2vec: universal speech emotion representation model

emotion2vec is the first universal speech emotion representation model. Through self-supervised pre-training, emotion2vec has the ability to extract emotion representation across different tasks, languages, and scenarios.

emotion2vec+: speech emotion recognition foundation model

emotion2vec+ is a series of foundational models for speech emotion recognition (SER). We aim to train a "whisper" in the field of speech emotion recognition, overcoming the effects of language and recording environments through data-driven methods to achieve universal, robust emotion recognition capabilities. The performance of emotion2vec+ significantly exceeds other highly downloaded open-source models on Hugging Face.

News

• [Jun. 2024] 🔧 We fix a bug in emotion2vec+. Please re-pull the latest code.
• [May. 2024] 🔥 Speech emotion recognition foundation model: emotion2vec+, with 9-class emotions has been released on Model Scope and Hugging Face. Check out a series of emotion2vec+ (seed, base, large) models for SER with high performance (We recommend this release instead of the Jan. 2024 release).
• [Jan. 2024] 9-class emotion recognition model with iterative fine-tuning from emotion2vec has been released in modelscope and FunASR.
• [Jan. 2024] emotion2vec has been integrated into modelscope and FunASR.
• [Dec. 2023] We release the paper, and create a WeChat group for emotion2vec.
• [Nov. 2023] We release code, checkpoints, and extracted features for emotion2vec.

Model Card

Original repository: https://github.com/ddlBoJack/emotion2vec

Model Scope repository: https://www.modelscope.cn/models/iic/emotion2vec_plus_large/summary

Hugging Face repository: https://huggingface.co/emotion2vec

FunASR repository: https://github.com/alibaba-damo-academy/FunASR