Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: ABROA : Audio-Based Room-Occupancy Analysis using Gaussian Mixtures and
  Hidden Markov Models   This paper outlines preliminary steps towards the development of an audio-
based room-occupancy analysis model. Our approach borrows from speech
recognition tradition and is based on Gaussian Mixtures and Hidden Markov
Models. We analyze possible challenges encountered in the development of such a
model, and offer several solutions including feature design and prediction
strategies. We provide results obtained from experiments with audio data from a
retail store in Palo Alto, California. Model assessment is done via
leave-two-out Bootstrap and model convergence achieves good accuracy, thus
representing a contribution to multimodal people counting algorithms.

14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
16
The categories of this paper are: stat
27
The categories of this paper are: comp-gas
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
17
The categories of this paper are: q-fin
26
The categories of this paper are: bayes-an
15
The categories of this paper are: nucl-ex
19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph
35
The categories of this paper are: mtrl-th
24
The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph