JANUS translates continuously spoken English and German into German, English, and Japanese. JANUS currently achieves 87% translation fidelity from English speech and 97% from German speech. We present the JANUS system along with comparative evaluations of its interchangeable processing components, with special emphasis on the connectionist modules.

JANUS translates continuously spoken English and German into German, English, and Japanese.

The features used in the spatial representations were abstracted from Herskovits (1986). The network was trained using the generalized delta rule (Rumelhart, Hinton, and Williams, 1986) on a set of patterns with four components, three syntactic and one semantic. The syntactic components are a pair of nouns separated by a locative preposition [NI-LP-N21, and the semantic component is a representation of the spatial relationship [SR1.

The features used in the spatial representations were abstracted from Herskovits (1986). The network was trained using the generalized delta rule (Rumelhart, Hinton, and Williams, 1986) on a set of patterns with four components, three syntactic and one semantic. The syntactic components are a pair of nouns separated by a locative preposition [NI-LP-N21, and the semantic component is a representation of the spatial relationship [SR1.

The network's performance was analyzed over several simulations with training sets in both English and German.

Computational Linguistics 169(2):79–85

Review of Machine Translation: Past, Present, Future

Hutchins not only presents machine translation research (such as problems of machine translation It is the theories, algorithms, and designs practical versus theoretical, empirical also not clear that the AI philosophy but also the history, goals, assumptions, versus perfectionist, and direct versus of understanding and meaning (p 327) and constraints of each project.

Hutchins not only presents machine translation research (such as problems of machine translation It is the theories, algorithms, and designs practical versus theoretical, empirical also not clear that the AI philosophy but also the history, goals, assumptions, versus perfectionist, and direct versus of understanding and meaning (p 327) and constraints of each project.

We address the problem of predicting a word from previous words in a sample of text. In particular, we discuss n-gram models based on classes of words. We also discuss several statistical algorithms for assigning words to classes based on the frequency of their co-occurrence with other words. We find that we are able to extract classes that have the flavor of either syntactically based groupings or semantically based groupings, depending on the nature of the underlying statistics.