Interaction between fast lexical access and word verification in large vocabulary continuous speech recognition

Recently a two step strategy for large vocabulary isolated word recognition has been successfully experimented. The first step consists in the hypothesization of a reduced set of word candidates on the basis of broad bottom-up features, while the second one is the verification of the hypotheses using more detailed phonetic knowledge. This paper deals with its extension to continuous speech. A tight integration between the two steps rather than a hierarchical approach has been investigated. The hypothesization and the verification modules are implemented as processes running in parallel. Both processes represent lexical knowledge by a tree. Each node of the hypothesization tree is labeled by one of 6 broad phonetic classes. The nodes of the verification tree are, instead, the states of sub-word HMMs. The two processes cooperate to detect word hypotheses along the sentence