Because of the complexity and high dimensionality of the problem, speech recognition—perhaps more than any other problem of current interest in network research—will profit from human neurophysiology, psychoacoustics and psycholinguistics: approaches based exclusively on engineering principles will provide only limited benefits. Despite the great power of current learning algorithms in homogeneous or unstructured networks, a number of difficulties in speech recognition seem to indicate that homogeneous networks taken alone will be insufficient for the task, and that structure—representing constraints—will also be required. In the biological system, the sources of such structure include developmental and evolutionary effects. Recent considerations of the evolutionary sources of neural structure in the human speech and language systems, including models of the interrelationship between speech motor system and auditory system, are analyzed with special reference to neural network approaches.
The practice of speech and language processing in China
