In this paper, we present an empirical study that utilizes morph-syntactical information to improve translation quality. With three kinds of language pairs matched according to morph-syntactical similarity or difference, we investigate the effects of various morpho-syntactical information, such as base form, part-of-speech, and the relative positional information of a word in a statistical mach...

A prefix normal word is a binary word with the property that no substring has more 1s than the prefix of the same length. This class of words is important in the context of binary jumbled pattern matching. In this paper we present an efficient algorithm for exhaustively listing the prefix normal words with a fixed length. The algorithm is based on the fact that the language of prefix normal wor...

A word recognition task was presented to 72 lower social class and 72 upper-middle social class kindergarteners who were randomly assigned to one of 3 methods (Word, Word Picture, or Word Object) and were asked to learn to recognize eight low frequency words. There were significant differences between lower and upper socioeconomic levels and among the three methods (p<.01). The Word Method was ...

Model M is a superior class-based n-gram model that has shown improvements on a variety of tasks and domains. In previous work with Model M, bigram mutual information clustering has been used to derive word classes. In this paper, we introduce a new word classing method designed to closely match with Model M. The proposed classing technique achieves gains in speech recognition word-error rate o...

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This paper describes an automatic word classiication system which uses a locally optimal annealing algorithm and average class mutual information. A new word-class representation, the structural tag is introduced and its advantages for use in statistical language modelling are presented. A summary of some results with the one million word lob corpus is given; the algorithm is also shown to disc...

We study finitely generated groups whose word problems are accepted by counter automata. We show that a group has word problem accepted by a blind n-counter automaton in the sense of Greibach if and only if it is virtually free abelian of rank n; this result, which answers a question of Gilman, is in a very precise sense an abelian analogue of the Muller-Schupp theorem. More generally, if G is ...

We describe an automatic word classiication system which uses a locally optimal annealing algorithm and average class mutual information. A new word-class representation, the structural tag is introduced and its advantages for use in statistical language modelling are presented. A summary of some results with the one million word lob corpus is given; the algorithm is also shown to discover the ...

In this paper we present a multi-class extension to our approach for modelling out-of-vocabulary (OOV) words [1]. Instead of augmenting the word search space with a single OOV model, we add several OOV models, one for each class of words. We present two approaches for designing the OOV word classes. The first approach relies on using common part-of-speech tags. The second approach is a data-dri...

In this paper we present a multi-class extension to our approach for modelling out-of-vocabulary (OOV) words [1]. Instead of augmenting the word search space with a single OOV model, we add several OOV models, one for each class of words. We present two approaches for designing the OOV word classes. The first approach relies on using common part-of-speech tags. The second approach is a data-dri...