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» Universal background model based speech recognition
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SPEECH
2008
97views more  SPEECH 2008»
14 years 9 months ago
A new approach for the adaptation of HMMs to reverberation and background noise
Looking at practical application scenarios of speech recognition systems several distortion effects exist that have a major influence on the speech signal and can considerably det...
Hans-Günter Hirsch, Harald Finster
DAGM
2008
Springer
14 years 11 months ago
Switching Linear Dynamic Models for Noise Robust In-Car Speech Recognition
Performance of speech recognition systems strongly degrades in the presence of background noise, like the driving noise in the interior of a car. We compare two different Kalman fi...
Björn Schuller, Martin Wöllmer, Tobias M...
ICIP
2004
IEEE
15 years 11 months ago
Statistical transformations of frontal models for non-frontal face verification
In the framework of a face verification system using local features and a Gaussian Mixture Model based classifier, we address the problem of non-frontal face verification (when on...
Conrad Sanderson, Samy Bengio
SP
2002
IEEE
114views Security Privacy» more  SP 2002»
14 years 9 months ago
HMM-based techniques for speech segments extraction
The goal of the speech segments extraction process is to separate acoustic events of interest (the speech segment to be recognised) in a continuously recorded signal from other par...
Waleed H. Abdulla
IROS
2007
IEEE
100views Robotics» more  IROS 2007»
15 years 4 months ago
Humanoid robot noise suppression by particle filters for improved automatic speech recognition accuracy
Automatic speech recognition on a humanoid robot is exposed to numerous known noises produced by the robot’s own motion system and background noises such as fans. Those noises i...
Florian Kraft, Matthias Wölfel