We present the newest implementation of the LINGSTAT machine-aided translation system. The moat signiflcsat change from earlier versions is a new set of modules that produce a draft translation of the document for the user to refer to or modify. This paper describes these modules, with special emphasis on an automatically trained lexicalized grammar used in the parsing module. Some preHminary results from the January 1994 ARPA evaluation are reported.
We present the newest implementation of the LINGSTAT machine-aided translation system. The moat signiflcsat change from earlier versions is a new set of modules that produce a draft translation of the document for the user to refer to or modify. This paper describes these modules, with special emphasis on an automatically trained lexicalized grammar used in the parsing module. Some preHminary results from the January 1994 ARPA evaluation are reported.
We present the newest implementation of the LINGSTAT machine-aided translation system. The moat signiflcsat change from earlier versions is a new set of modules that produce a draft translation of the document for the user to refer to or modify. This paper describes these modules, with special emphasis on an automatically trained lexicalized grammar used in the parsing module. Some preHminary results from the January 1994 ARPA evaluation are reported.
The goal of this study is to evaluate the potential for using large vocabulary continuous speech recognition as an engine for automatically classifying utterances according to the language being spoken. The problem of language identification is often thought of as being separate from the problem of speech recognition. But in this paper, as in Dragon's earlier work on topic and speaker identification, we explore a unifying approach to all three message classification problems based on the underlying stochastic process which gives rise to speech. We discuss the theoretical framework upon which our message classification systems are built and report on a series of experiments in which this theory is tested, using large vocabulary continuous speech recognition to distinguish English from Spanish.
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