Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multimodal Polynomial Fusion for Detecting Driver Distraction   Distracted driving is deadly, claiming 3,477 lives in the U.S. in 2015 alone.
Although there has been a considerable amount of research on modeling the
distracted behavior of drivers under various conditions, accurate automatic
detection using multiple modalities and especially the contribution of using
the speech modality to improve accuracy has received little attention. This
paper introduces a new multimodal dataset for distracted driving behavior and
discusses automatic distraction detection using features from three modalities:
facial expression, speech and car signals. Detailed multimodal feature analysis
shows that adding more modalities monotonically increases the predictive
accuracy of the model. Finally, a simple and effective multimodal fusion
technique using a polynomial fusion layer shows superior distraction detection
results compared to the baseline SVM and neural network models.

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The categories of this paper are: hep-ph
9
The categories of this paper are: nlin
34
The categories of this paper are: chem-ph
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
31
The categories of this paper are: ao-sci
3
The categories of this paper are: physics
13
The categories of this paper are: quant-ph
36
The categories of this paper are: cmp-lg
14
The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th
11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph