2aSC5. Annealing in a genetic algorithm for task-dynamic recovery from speech acoustics.

Session: Tuesday Morning, May 14

Time: 9:30

Author: Richard S. McGowan
Location: Haskins Labs., 270 Crown St., New Haven, CT 06511


Genetic algorithms, as they have been used for recovery of task-dynamic parameters [R. S. McGowan, ``Recovering articulatory movement from formant frequency trajectories using task dynamics and a genetic algorithm,'' Speech Commun. 14, 19--49 (1994)], can take some time to converge, which means that expensive function evaluations are necessary to obtain optimum solutions. In previous experiments, each task dynamic- target was always given 6 bits in the chromosome. In the tests reported here, the number of bits in the chromosome string representing target positions was made a function of generation, with the range of the targets remaining constant to see whether an annealing process with ever increasing resolution would speed convergence to a good fitness maximum. Results show that annealing can be helpful in speeding convergence, although not all annealing schedules help. This procedure is related to simulated annealing where the temperature of the search is decreased as the search progresses. It is also related to codebook look-up used in the inverse problem, where vocal tract shapes that produce speech close to that of the data are accessed to initialize a subsequent optimization procedure. [Work supported by NIH Grant DC-01247 to Haskins Laboratories.]

from ASA 131st Meeting, Indianapolis, May 1996