Influence of autocorrelation lag ranges on robust speech recognition
MetadataShow full item record
It is generally believed that the lower-lag autocorrelation coefficients carry information about the spectral envelop and the higher-lag autocorrelation coefficients are more related to pitch information. In this paper, we use lower-lag and higher-lag ranges of the autocorrelation function separately for deriving speech recognition features, and investigate their role in terms of speech recognition performance. The state-of-the-art MFCC features use the whole autocorrelation function in their computation and are used here as a benchmark in our experiments. Our recognition results from the Aurora II corpus show that the higher-lag autocorrelation coefficients perform as well as the whole autocorrelation function for clean speech, and provide better performance for noisy speech, while lower-lag autocorrelation coefficients are not as effective in this aspect.
© 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.