At The 15th International Workshop on Acoustic Signal Enhancemen 2016 (IWAENC) held September 13-16 in Xi’an, China, Audio Analysis Lab member Prof. Mads Græsbøll Christensen gave a keynote talk about the lab’s work. The slides can be downloaded here. IWAENC is a leading workshop in the signal processing community addressing the problems of acoustic signal processing.

Title: Statistical Parametric Speech Processing

Abstract: Parametric speech models have been around for many years but have always had their detractors. Two common arguments against such models are that it is too difficult to find their parameters and that the models do not take the complicated nature of real signals into account. In recent years, significant advances have been made in speech models and robust estimation using statistical principles, and it has been demonstrated that, regardless of any deficiencies in the model, the parametric methods outperform the more commonly used non-parametric methods (e.g., autocorrelation-based methods) for problems like pitch estimation. In this talk, state-of-the-art parametric speech models and statistical estimators for finding their parameters will be presented and their pros and cons discussed. The merits of the statistical, parametric approach to speech modeling will be demonstrated by showing how otherwise complicated problems can be solved comparably easily this way. Examples of such problems are pitch estimation for non-stationary speech, distortionless speech enhancement, noise statistics estimation, speech segmentation, multi-channel modeling, and model-based localization and beamforming with microphone arrays.