Abstract book (pdf) - ICPR 2010

of the inner product matrices into diagonal matrices and orthonormal and into diagonal and upper triangular matrices.
Next we describe the estimation of the inner product matrices from measured data as an optimization process on the homogeneous
space of upper triangular matrices. We show that the decomposition leads to simple forms of partial derivatives
that are commonly used in optimization algorithms. Using the group theoretical parametrization ensures also that all intermediate
estimates of the inner product matrix are symmetric and positive definite. Finally we apply the method to a
problem from psychophysics where the color perception properties of an observer are characterized with the help of color
matching experiments. We will show that measurements from color weak observers require the enforcement of the positive-definiteness
of the matrix with the help of the manifold optimization technique.
13:30-16:30, Paper ThBCT9.21
Rethinking Algorithm Design and Development in Speech Processing
Stadelmann, Thilo, Univ. of Marburg
Wang, Yinghui, Univ. of Marburg
Smith, Matthew, Univ. of Hannover
Ewerth, Ralph, Univ. of Marburg
Freisleben, Bernd, Univ. of Marburg
Speech processing is typically based on a set of complex algorithms requiring many parameters to be specified. When
parts of the speech processing chain do not behave as expected, trial and error is often the only way to investigate the reasons.
In this paper, we present a research methodology to analyze unexpected algorithmic behavior by making (intermediate)
results of the speech processing chain perceivable and intuitively comprehensible by humans. The workflow of the
process is explicated using a real-world example leading to considerable improvements in speaker clustering. The described
methodology is supported by a software toolbox available for download.
13:30-16:30, Paper ThBCT9.22
Phone-Conditioned Suboptimal Wiener Filtering
Gonzalez-Caravaca, Guillermo, Univ. Autonoma de Madrid
Toledano, Doroteo, Univ. Autonoma de Madrid
Puertas, Maria, Univ. Autonoma de Madrid
A novel way of managing the compromise between noise reduction and speech distortion in Wiener filters is presented. It
is based on adjusting the amount of noise reduced, and therefore the speech distortion introduced, on a phone-by-phone
basis. We show empirically that optimal Wiener filters produce different amounts of speech distortion for different phones.
Therefore we propose a phone-conditioned suboptimal Wiener filter that uses different amounts of noise reduction for
each phone, based on a previous estimation of the amount of distortion introduced. Speech recognition results have shown
that phone conditioning suboptimal Wiener filtering can provide almost a 5% additional relative improvement in word
accuracy over comparable optimal Wiener filtering.
13:30-16:30, Paper ThBCT9.23
Geodesic Active Fields on the Sphere
Zosso, Dominique, École Pol. Fédérale de Lausanne
Thiran, Jean-Philippe, École Pol. Fédérale de Lausanne
In this paper, we propose a novel method to register images defined on spherical meshes. Instances of such spherical
images include inflated cortical feature maps in brain medical imaging or images from omni directional cameras. We apply
the Geodesic Active Fields (GAF) framework locally at each vertex of the mesh. Therefore we define a dense deformation
field, which is embedded in a higher dimensional manifold, and minimize the weighted Polyakov energy. While the
Polyakov energy itself measures the hyper area of the embedded deformation field, its weighting allows to account for the
quality of the current image alignment. Iteratively minimizing the energy drives the deformation field towards a smooth
solution of the registration problem. Although the proposed approach does not necessarily outperform state-of-the-art
methods that are tightly tailored to specific applications, it is of methodological interest due to its high degree of flexibility
and versatility.
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