Title :
Extending features for automatic speech recognition by means of auditory modelling
Author :
Szepannek, Gero ; Harczos, Tamas ; Klefenz, Frank ; Weihs, Claus
Author_Institution :
Dept. of Stat., Dortmund Univ. of Technol., Dortmund, Germany
Abstract :
When investigating the benefit of auditory modelling for automatic speech recognition applications typically different features or auditory simulation models are compared. In this work the attempt of combining several auditory model based feature extraction schemes is pursued, as well as their further combination with standard MFCC features.
Keywords :
feature extraction; speech recognition; MFCC features; auditory simulation models; automatic speech recognition; feature extraction schemes; Delays; Feature extraction; Hidden Markov models; Psychoacoustic models; Speech; Speech recognition; Standards;
Conference_Titel :
Signal Processing Conference, 2009 17th European
Conference_Location :
Glasgow
Print_ISBN :
978-161-7388-76-7