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27 Robust Speech Processing as an Inverse Problem

This section addresses the inverse problem in robust speech processing. A problem that speaker and speech recognition systems regularly encounter in the commercialized applications is the dramatic degradation of performance due to the mismatch of the training and operating environments. | Mammone R.J. Zhang X. Robust Speech Processing as an Inverse Problem Digital Signal Processing Handbook Ed. Vijay K. Madisetti and Douglas B. Williams Boca Raton CRC Press LLC 1999 1999 by CRC Press LLC 27 Robust Speech Processing as an Inverse Problem Richard J. Mammone Rutgers University Xiaoyu Zhang Rutgers University 27.1 Introduction 27.2 Speech Production and Spectrum-Related Parameterization 27.3 Template-Based Speech Processing 27.4 Robust Speech Processing 27.5 Affine Transform 27.6 Transformation of Predictor Coefficients Deterministic Convolutional Channel as a Linear Transform Additive Noise as a Linear Transform 27.7 Affine Transform of Cepstral Coefficients 27.8 Parameters of Affine Transform 27.9 Correspondence of Cepstral Vectors References 27.1 Introduction This section addresses the inverse problem in robust speech processing. A problem that speaker and speech recognition systems regularly encounter in the commercialized applications is the dramatic degradation of performance due to the mismatch of the training and operating environments. The mismatch generally results from the diversity of the operating environments. For applications over the telephone network the operating environments may vary from offices and laboratories to household places and airports. The problem becomes worse when speech is transmitted over the wireless network. Here the system experiences cross-channel interferences in addition to the channel and noise degradations that exist in the regular telephone network. The key issue in robust speech processing is to obtain good performance regardless of the mismatch in the environmental conditions. The inverse problem in this sense refers to the process of modeling the mismatch in the form of a transformation and resolving it via an inverse transformation. In this section we introduce the method of modeling the mismatch as an affine transformation. Before getting into the details of the inverse problem in robust speech processing