Ina Roesiger author Sabrina Stehwien author Arndt Riester author Ngoc Thang Vu author 2017-09 text Association for Computational Linguistics Copenhagen, Denmark conference publication Adding manually annotated prosodic information, specifically pitch accents and phrasing, to the typical text-based feature set for coreference resolution has previously been shown to have a positive effect on German data. Practical applications on spoken language, however, would rely on automatically predicted prosodic information. In this paper we predict pitch accents (and phrase boundaries) using a convolutional neural network (CNN) model from acoustic features extracted from the speech signal. After an assessment of the quality of these automatic prosodic annotations, we show that they also significantly improve coreference resolution. roesiger-etal-2017-improving 10.18653/v1/W17-4610 https://aclanthology.org/W17-4610 2017-09 78 83