@inproceedings{kaplan-2020-may,
    title = "May {I} Ask Who{'}s Calling? Named Entity Recognition on Call Center Transcripts for Privacy Law Compliance",
    author = "Kaplan, Micaela",
    editor = "Xu, Wei  and
      Ritter, Alan  and
      Baldwin, Tim  and
      Rahimi, Afshin",
    booktitle = "Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2020.wnut-1.1",
    doi = "10.18653/v1/2020.wnut-1.1",
    pages = "1--6",
    abstract = "We investigate using Named Entity Recognition on a new type of user-generated text: a call center conversation. These conversations combine problems from spontaneous speech with problems novel to conversational Automated Speech Recognition, including incorrect recognition, alongside other common problems from noisy user-generated text. Using our own corpus with new annotations, training custom contextual string embeddings, and applying a BiLSTM-CRF, we match state-of- the-art results on our novel task.",
}