Microphone-Independent Robust Signal Processing Using Probabilistic Optimum Filtering

A new mapping algorithm for speech recognition relates the features of simultaneous recordings of clean and noisy speech. The model is a piecewise nonfinear transformation appfied to the noisy speech feature. The transformation is a set of multidimensional linear least-squares filters whose outputs are combined using a conditional Gaussian model. The algorithm was tested using SRI's DECIPHERTM speech recognition system [1-5]. Experimental results show how the mapping is used to reduce recognition errors when the training and testing acoustic environments do not match.

• Type: Conference
• Year: 1994
• Where: NAACL
• Authors: Leonardo Neumeyer, Mitch Weintraub
• Keywords: NAACL 1994, NAACL 2007, Noisy Speech, Noisy Speech Feature, Speech Recognition