@inproceedings{morales-etal-2018-linguistically,
    title = "A Linguistically-Informed Fusion Approach for Multimodal Depression Detection",
    author = "Morales, Michelle  and
      Scherer, Stefan  and
      Levitan, Rivka",
    editor = "Loveys, Kate  and
      Niederhoffer, Kate  and
      Prud{'}hommeaux, Emily  and
      Resnik, Rebecca  and
      Resnik, Philip",
    booktitle = "Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic",
    month = jun,
    year = "2018",
    address = "New Orleans, LA",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W18-0602",
    doi = "10.18653/v1/W18-0602",
    pages = "13--24",
    abstract = "Automated depression detection is inherently a multimodal problem. Therefore, it is critical that researchers investigate fusion techniques for multimodal design. This paper presents the first-ever comprehensive study of fusion techniques for depression detection. In addition, we present novel linguistically-motivated fusion techniques, which we find outperform existing approaches.",
}