SER Wav2vec2 Large Xlsr 53 Eng Zho Adults

🚀 Cross-Lingual Cross-Age Group Adaptation for Low-Resource Elderly Speech Emotion Recognition

This project fine-tunes a model for speech emotion recognition on English and Chinese data from adult speakers, aiming to address low - resource elderly speech emotion recognition.

🚀 Quick Start

The model is a fine - tuned version of facebook/wav2vec2-large-xlsr-53 on English and Chinese data from adult speakers. It is trained on the training sets of CREMA-D, ESD, IEMOCAP, and TESS.

When using this model, make sure that your speech input is sampled at 16kHz.

The scripts used for training and evaluation can be found here: https://github.com/HLTCHKUST/elderly_ser/tree/main

📚 Documentation

Evaluation Results

For the details (e.g., the statistics of train, valid, and test data), please refer to our paper on arXiv. It also provides the model's speech emotion recognition performances on: English-All, Chinese-All, English-Elderly, Chinese-Elderly, English-Adults, Chinese-Adults.

📄 License

This project is licensed under the CC - BY - SA 4.0 license.

📖 Citation

Our paper will be published at INTERSPEECH 2023. In the meantime, you can find our paper on arXiv. If you find our work useful, please consider citing our paper as follows:

@misc{cahyawijaya2023crosslingual,
      title={Cross-Lingual Cross-Age Group Adaptation for Low-Resource Elderly Speech Emotion Recognition}, 
      author={Samuel Cahyawijaya and Holy Lovenia and Willy Chung and Rita Frieske and Zihan Liu and Pascale Fung},
      year={2023},
      eprint={2306.14517},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Additional Information