Model overview
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. This version (emotion2vec_plus_large) uses a large-scale pseudo-labeled data for finetuning to obtain a large size model (~300M), and currently supports the following categories: 0: angry 1: disgusted 2: fearful 3: happy 4: neutral 5: other 6: sad 7: surprised 8: unknown GitHub Repo: emotion2vec |Model|⭐Model Scope|🤗Hugging Face|Fine-tuning Data (Hours)| |:---:|:-------------:|:-----------:|:-------------:| |emotion2vec|Link|Link|/| emotion2vec+ seed|Link|Link|201| emotion2vec+ base|Link|Link|4788| emotion2vec+ large|Link|Link|42526|
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
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Source prices & cost analysis
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Public benchmarks & run configuration
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Sources & traceability
许可证：other。模型介绍与第三方评测均以原来源的具体版本和方法为准。