The paper continues the authors' investigation of machines that adaptively acquire language through interaction with a complex environment. In particular, this work focuses on the problem of spoken word acquisition, using our proposed principles to motivate a method to govern the emergence of word symbols from the speech signal. The mechanism involves a connectionist network embedded in a feedback control system. The resulting system has two unique characteristics. First, no text is utilized by the device, in contrast to all other speech understanding systems. Second, the vocabulary and grammar is unconstrained, being acquired by the device during the course of performing its task. This is also in contrast to all other systems, in which the salient vocabulary and grammar are preprogrammed. A rudimentary baseline experiment is described, involving 1105 natural language utterances in an Automated Call Routing application scenario.
ASJC Scopus subject areas
- Acoustics and Ultrasonics
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering