A system for understanding time utterances spoken in German language is presented. Stochastic models contain the knowledge in the semantic, syntactic and acousticphonetic levels. An adequate semantic representation allows the integration of these models within a one-pass Viterbi search. The simultaneous use of all knowledge sources for the search procedure results in the smallest possible search space for the determination of the most probable semantic content accurately following the Bayes classification rule. Both the recognition accuracy and the computing speed facilitate a realistic application. Keywords: speech recognition, language understanding, spoken man-machine-dialogue, stochastic models, onepass search, representation of syntactic and semantic knowledge 1. INTRODUCTION Using speech as a communication medium in technical systems, the syntax and the semantics of the spoken utterances are often strongly constrained within a certain domain. The research system described in t...

The growth of information available to learning systems and the increasing complexity of learning tasks determine the need for devising algorithms that scale well with respect to all learning parameters. In the context of supervised sequential learning, the Viterbi algorithm plays a fundamental role, by allowing the evaluation of the best (most probable) sequence of labels with a time complexity linear in the number of time events, and quadratic in the number of labels. In this paper we propose CarpeDiem, a novel algorithm allowing the evaluation of the best possible sequence of labels with a sub-quadratic time complexity. 1 We provide theoretical grounding together with solid empirical results supporting two chief facts. CarpeDiem always finds the optimal solution requiring, in most cases, only a small fraction of the time taken by the Viterbi algorithm; meantime, CarpeDiem is never asymptotically worse than the Viterbi algorithm, thus confirming it as a sound replacement.

We outline an implementation of Viterbi beam search that incorporates layered bigrams. Layered bigrams are class bigrams in which some nodes are themselves bigrams, resulting in a recursive structure. The implementation is in C ++ and involves a hierarchy of classes. The paper outlines the main concepts and the corresponding C ++ classes.