![](bg5.png)
of biases into consideration when we apply the filter-
ing system to recognition system.
5 DISCUSSIONS AND
CONCLUSIONS
In this paper, we proposed parameter setting of noise
reduction filter utilizing speech recognition system.
The algorithm is simple, and the adequate parameter
could be obtained throughout the experiments. As the
proposed method does not use the relation between
the signal and noise, it is expected that the application
range of the proposed method is large. By using our
method, even if we only have the single-channel noisy
signal, we can evaluate whether the parameter is ade-
quate or not. The proposed method does not require
to estimate the noise in advance.
Experimental results also give us some visions to
be considered with regard to our approach. For in-
stance, the nonlinear relation between the filter pa-
rameter and the recognition result is an important
problem. The obtained recognition result sometimes
drastically moves with a tiny parameter change due to
the nonlinearity between the filtering and recognition
system. Our approach will be more useful when a fil-
ter has the linear relationship between the parameter
change and the filtering error.
For future works, we would like to investigate the
relation between the adequate recognition system and
filtering system. Theoretical analyses are also re-
quired. We aim to apply this criterion to other sys-
tems. Applications for robot auditory will also be
considered.
ACKNOWLEDGEMENTS
This research was supported by Special Coordi-
nation Funds for Promoting Science and Technol-
ogy, by research grant from Support Center for
Advanced TelecommunicationsTechnology Research
(SCAT), by the Ministry of Education, Science,
Sports and Culture, Grant-in-Aid for Young Scientists
(B), 22700186, 2010. and by the Ministry of Edu-
cation, Science, Sports and Culture, Grant-in-Aid for
Young Scientists (B), 20700168, 2008. This research
was also supported by the CREST project “Founda-
tion of technology supporting the creation of digital
media contents” of JST, and the Global-COE Pro-
gram,“Global Robot Academia”, Waseda University.
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