Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Modeling State-Conditional Observation Distribution using Weighted
  Stereo Samples for Factorial Speech Processing Models   This paper investigates the effectiveness of factorial speech processing
models in noise-robust automatic speech recognition tasks. For this purpose,
the paper proposes an idealistic approach for modeling state-conditional
observation distribution of factorial models based on weighted stereo samples.
This approach is an extension to previous single pass retraining for ideal
model compensation which is extended here to support multiple audio sources.
Non-stationary noises can be considered as one of these audio sources with
multiple states. Experiments of this paper over the set A of the Aurora 2
dataset show that recognition performance can be improved by this
consideration. The improvement is significant in low signal to noise energy
conditions, up to 4% absolute word recognition accuracy. In addition to the
power of the proposed method in accurate representation of state-conditional
observation distribution, it has an important advantage over previous methods
by providing the opportunity to independently select feature spaces for both
source and corrupted features. This opens a new window for seeking better
feature spaces appropriate for noisy speech, independent from clean speech
features.

8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
17
The categories of this paper are: q-fin
3
The categories of this paper are: physics
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
26
The categories of this paper are: bayes-an