Massively Parallel Parsing in ΦDmDialog: Integrated Architecture for Parsing Speech Inputs

This paper describes the parsing scheme in the 𝛷DmDialog speech-to-speech dialog translation system, with special emphasis on the integration of speech and natural language processing. We propose an integrated architecture for parsing speech inputs based on a parallel marker-passing scheme and attaining dynamic participation of knowledge from the phonological-level to the discourse-level. At the phonological level, we employ a stochastic model using a transition matrix and a confusion matrix and markers which carry a probability measure. At a higher level, syntactic/semantic and discourse processing, we integrate a case-based and constraint-based scheme in a consistent manner so that a priori probability and constraints, which reflect linguistic and discourse factors, are provided to the phonological level of processing. A probability/cost-based scheme in our model enables ambiguity resolution at various levels using one uniform principle.