Speech Inverse Filtering by Simulated Annealing Algorithm

The purpose of this study is to develop one solution to the speech inverse filtering problem. A new efficient articulatory speech analysis scheme, identifying the articulatory parameters from the acoustic speech waveforms, was induced. The algorithm is known as simulated annealing, which is constrained to avoid non-unique solutions and local minima problems. The constraints are determined by the articulatory-to-acoustic transformation function and the boundary conditions for the articulatory parameters. The cost function is defined as a percentage of the weighted least-absolute-value error distance between the first four formant frequencies of the articulatory model and the first four formant frequencies determined from speech analysis. It is used to optimize the vocal tract parameters to match a specified set of formant characteristics. A 1% error criterion was found to be both practical and achievable.