Authors:
Tomomi Abe
1
;
Mitsuharu Matsumoto
2
and
Shuji Hashimoto
1
Affiliations:
1
Waseda university, Japan
;
2
The University of Electro-Communications, Japan
Keyword(s):
Speech recognition system, Parameter optimization, Recognition-based approach, Nonlinear filter.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Informatics in Control, Automation and Robotics
;
Methodologies and Methods
;
Multimedia
;
Multimedia Signal Processing
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing, Sensors, Systems Modeling and Control
;
Soft Computing
;
Speech Recognition
;
Telecommunications
Abstract:
This paper describes parameter setting of noise reduction filter using speech recognition system. Parameter setting problem is usually solved by maximization or minimization of some objective evaluation functions such as correlation and statistical independence. However, when we consider a single-channel noisy signal, it is difficult to employ such objective functions. It is also difficult to employ them when we consider impulsive noise because its duration is very small to use this assumption. To solve the problems, we directly use a speech
recognition system as evaluation function for parameter setting. As an example, we employ time-frequency e-filter and Julius as a filtering system and a speech recognition system, respectively. The experimental results show that the proposed approach has a potential to set the parameter in unknown environments.