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README.md
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## For a better performance version, please refer to
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[hughlan1214/
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## Model description
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For a better performance version, please refer to [hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fin-
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The model was obtained through feature extraction using [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) and underwent several rounds of fine-tuning. It predicts the 7 types of emotions contained in speech, aiming to lay the foundation for subsequent use of human micro-expressions on the visual level and context semantics under LLMS to infer user emotions in real-time.
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## For a better performance version, please refer to
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[hughlan1214/SER_wav2vec2-large-xlsr-53_240304_fine-tuned1.1](https://huggingface.co/hughlan1214/SER_wav2vec2-large-xlsr-53_240304_fine-tuned1.1)
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## Model description
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For a better performance version, please refer to [hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fin-tuned1.1](https://huggingface.co/hughlan1214/Speech_Emotion_Recognition_wav2vec2-large-xlsr-53_240304_SER_fin-tuned1.1)
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The model was obtained through feature extraction using [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) and underwent several rounds of fine-tuning. It predicts the 7 types of emotions contained in speech, aiming to lay the foundation for subsequent use of human micro-expressions on the visual level and context semantics under LLMS to infer user emotions in real-time.
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