The impact of spectral and energy mismatch on the Aurora2 digit recognition task

Within the Aurora2 experimental framework, the aim of this study is to determine what the relative contributions of spectral shape and energy features are to the mismatch observed between clean training and noisy test data. In addition to measurements on the baseline Aurora2 system, recognition performance was also evaluated after the application of time domain noise reduction (TDNR) and histogram normalisation (HN) in the cepstral domain. The results indicate that, for the Aurora2 digit recognition task, TDNR, HN, as well as a combination of the two techniques achieve higher recognition rates by reducing the mismatch in the energy part of acoustic feature space. The corresponding mismatch reduction in the spectral shape features yields hardly any gain in recognition performance.