Deeper spoken language understanding for man-machine dialogue on broader application domains

摘要

LOGUS is a French-speaking spoken language understanding (SLU) system which carries out a deeper analysis than those achieved by standard concept spotters. It is designed for multi-domain conversational systems or for systems that are working on complex application domains. Based on a logical approach, the system adapts the ideas of incremental robust parsing to the issue of SLU. The paper provides a detailed description of the system as well as results from two evaluation campaigns that concerned all of current French-speaking SLU systems. The observed error rates suggest that our logical approach can stand comparison with concept spotters on restricted application domains, but also that its behaviour is promising for larger domains. The question of the generality of the approach is precisely addressed by our current investigations on a new task: SLU for an emotional robot companion for young hospital patents.