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We describe a series o,f five statistical models o,f the translation process and give algorithms,for estimating the parameters o,f these models given a set o,f pairs o,f sentences that are translations o,f one another. We define a concept o,f word-byword alignment between such pairs o,f sentences. For any given pair of such sentences each o,f our models(More)
The concept of maximum entropy can be traced back along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statistical estimation and pattern recognition. In this paper, we describe a method for statistical modeling based on maximum(More)
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 coo occurrence with other words. We nd that we are able to extract classes that have the avor of(More)
In this paper, we present a statistical approach to machine translation. We describe the application of our approach to translation from French to English and give preliminary results. The field of machine translation is almost as old as the modern digital computer. In 1949 Warren Weaver suggested that the problem be attacked with statistical methods and(More)
—We present a technique for constructing random fields from a set of training samples. The learning paradigm builds increasingly complex fields by allowing potential functions, or features, that are supported by increasingly large subgraphs. Each feature has a weight that is trained by minimizing the Kullback-Leibler divergence between the model and the(More)
We present an estimate of an upper bound of 1.75 bits for the entropy of characters in printed English, obtained by constructing a word trigram model and then computing the cross-entropy between this model and a balanced sample of English text. We suggest the well-known and widely available Brown Corpus of printed English as a standard against which to(More)
An approach to automatic translation is outlined that utilizes technklues of statistical inl'ormatiml extraction from large data bases. The method is based on the availability of pairs of large corresponding texts that are translations of each other. In our case, the iexts are in English and French. Fundamental to the technique is a complex glossary of(More)
We describe a statistical technique for assigning senses to words. An instance of a word is assigned a sense by asking a question about the context in which the word appears. The question is constructed to have high mutual information with the translation of that instance in another language. When we incorporated this method of assigning senses into our(More)
We present an overview of Candide, a system for automatic translation of French text to English text. Candide uses methods of information theory and statistics to develop a probability model of the translation process. This model, which is made to accord as closely as possible with a large body of French and English sentence pairs, is then used to generate(More)