  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.
