Spoken-Conversation-Question-Answering

• Spoken conversation question answering benchmark dataset is from BaiduDisk, the password is 5s6r. More deatils of this dataset can be found at: NAACL 2022 Paper "End-to-end Spoken Conversational Question Answering: Task, Dataset and Model".

Citation

If you found this code/work to be useful in your own research, please considering citing the following:

@inproceedings{you2022end,
    title={End-to-end Spoken Conversational Question Answering: Task, Dataset and Model},
    author={You, Chenyu and Chen, Nuo and Liu, Fenglin and Ge, Shen and Wu, Xian and Zou, Yuexian},
    booktitle={Findings of the Association for Computational Linguistics: NAACL 2022},
    year={2022},
}

@inproceedings{you2021mrd,
  title={MRD-Net: Multi-Modal Residual Knowledge Distillation for Spoken Question Answering.},
  author={You, Chenyu and Chen, Nuo and Zou, Yuexian},
  booktitle={IJCAI},
  year={2021}
}

@inproceedings{you2022selfsupervised,
    title={Self-supervised Contrastive Cross-Modality Representation Learning for Spoken Question Answering},
    author={You, Chenyu and Chen, Nuo and Zou, Yuexian},
    booktitle={Findings of the Association for Computational Linguistics: EMNLP 2021},
    year={2021},
}

@inproceedings{you2020contextualized,
  title={Contextualized attention-based knowledge transfer for spoken conversational question answering},
  author={You, Chenyu and Chen, Nuo and Zou, Yuexian},
  booktitle={INTERSPEECH},
  year={2021}
}

@inproceedings{you2021knowledge,
  title={Knowledge distillation for improved accuracy in spoken question answering},
  author={You, Chenyu and Chen, Nuo and Zou, Yuexian},
  booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2021}
}

Contact

If you have any questions, please contact [email protected].