The authors present JANUS, a speech-to-speech translation system that utilizes diverse processing strategies including dynamic programming, stochastic techniques, connectionist learning, and traditional AI knowledge representation approaches. JANUS translates continuously spoken English utterances into Japanese and German speech utterances. The overall system performance on a corpus of conference registration conversations is 87%. Two versions of JANUS are compared: one using a LR parser (JANUS 1) and one using a connectionist parser (JANUS 2). Performance results were mixed, with JANUS 1 deriving benefit from a tighter language model and JANUS 2 benefitting from greater flexibility.
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