A powerful approach for handling uncertainty in observations is to modify the statistical model of the data to appropriately reflect this uncertainty. For the task of noise robust speech recognition, this requires modifying an underlying ”clean” acoustic model to be representative of speech in a particular target acoustic environment. This chapter describes the underlying concepts of model-base...

Estimators for speech enhancement by using wavelet transform is the new technique which is proposed in this paper. Here, we proposed a new set of estimators called magnitude square spectrum estimators beyond the conventional magnitude, power estimators using wavelet transform. Maximum a posteriori(MAP), Minimum Mean Square Error(MMSE) Estimators are derived using hard masking then Soft Masking ...

In meetings or noisy public places, often a number of speakers are active simultaneously and the sources of interest need to be separated from interfering speech in order to be robustly recognized. Independent component analysis (ICA) has proven to be a valuable tool for this purpose. However, under difficult environmental conditions, ICA outputs may still contain strong residual components of ...

Uncertainty propagation is an established approach to handle noisy and reverberant conditions in automatic speech recognition (ASR), but it has little been studied for speaker recognition so far. Yu et al. recently proposed to propagate uncertainty to the Baum-Welch (BW) statistics without changing the posterior probability of each mixture component. They obtained good results on a small datase...