Speech Communication - Special issue on interactive voice technology for telecommunication applications (IVITA '96)
Grammar fragment acquisition using syntactic and semantic clustering
Speech Communication
Robust numeric recognition in spoken language dialogue
Speech Communication - Special issue on noise robust ASR
Semantic information processing of spoken language: how may I help you?
Proceedings of the 8th international conference on Intelligent user interfaces
Stochastic Finite-State Models for Spoken Language MachineTranslation
Machine Translation
Semantic analysis for a speech user interface in an intelligent tutoring system
Proceedings of the 9th international conference on Intelligent user interfaces
Modeling Complex Spoken Dialog
Computer
An active approach to spoken language processing
ACM Transactions on Speech and Language Processing (TSLP)
Multi-stream Fusion for Speaker Classification
Speaker Classification I
MAP adaptation of stochastic grammars
Computer Speech and Language
| Hi-index | 4.10 |
Traditional menu-driven speech recognition systems force users to learn the machine's jargon, but many people can't or won't navigate such highly structured interactions. AT&T's "How May I Help You?" technology shifts the burden to the machine by requiring it to adapt to human language and understand what people actually say rather than what a system designer expects them to say. For a given task, it is more crucial to recognize and understand some linguistic events than others. The authors have developed algorithms that automatically learn the salient words, phrases, and grammar fragments for a given task far more reliably than other methods.