Importance

Loading Importance Indicators...

Abstract

Spoken-language instruction method and apparatus employ context-based speech recognition for instruction and evaluation, particularly language instruction and language fluency evaluation. A system can administer a lesson, and particularly a language lesson, and evaluate performance in a natural interactive manner while tolerating strong foreign accents, and produce as an output a reading quality score. A finite state grammar set corresponding to the range of word sequence patterns in the lesson is employed as a constraint on a hidden Markov model (HMM) search apparatus in an HMM speech recognizer which includes a set of hidden Markov models of target-language narrations produced by native speakers of the target language. The invention is preferably based on use of a linguistic context-sensitive speech recognizer. The invention includes a system with an interactive decision mechanism which employs at least three levels of error tolerance to simulate a natural level of patience in human-based interactive instruction. A system for a reading phase is implemented through a finite state machine having at least four states which recognizes reading error at any position in a script and which employs a first set of actions. A related system for an interactive question phase is implemented through a finite state machine, but which recognizes reading errors as well as incorrect answers while invoking a second set of actions. A linguistically-sensitive utterance endpoint detector is provided for judging termination of a spoken utterance to simulate human turn-taking in conversational speech.

Loading the Abstract Image...

First Claim