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EN
This paper summarizes the results of my Master's thesis and the main points of a talk I presented at the seminar of the Department of Applied Logic at the Adam Mickiewicz University in Poznań.It gives a short overview of the structure of German compounds and newer research concerning the role of the so-called interfixes. After an introduction to the concept of finite-state transducers the construction of a transducer used for naive compound segmentation is described. Tag-based finite-state methods for the further analysis of the found segments are given and discussed. Distributional transducer rules, for the construction of which I assume the existence of local and global morphological contexts, are proposed as means of disambiguation of the analyzed naive segmentation results. 
PL
This paper summarizes the results of my Master's thesis and the main points of a talk I presented at the seminar of the Department of Applied Logic at the Adam Mickiewicz University in Poznań.It gives a short overview of the structure of German compounds and newer research concerning the role of the so-called interfixes. After an introduction to the concept of finite-state transducers the construction of a transducer used for naive compound segmentation is described. Tag-based finite-state methods for the further analysis of the found segments are given and discussed. Distributional transducer rules, for the construction of which I assume the existence of local and global morphological contexts, are proposed as means of disambiguation of the analyzed naive segmentation results.
EN
The intention of this article is to provide a concise introduction to the basic mathematical concepts of statistical translation models as they were introduced by Brown et al. (1993) in their groundbreaking work The Mathematics of Statistical Machine Translation: Parameter Estimation. We concentrate on a simplified description of the first two translation models known as IBM Model 1 and 2. It is one major aim of this work to serve as tutoring material for students of computational linguistics, mathematics or computer science and therefore a lot of comments, additional examples and step-by-step explanations are given, augmenting the original formula by Brown et al. (1993). For both discussed models the calculations for a small parallel corpus are described in detail.
PL
The intention of this article is to provide a concise introduction to the basic mathematical concepts of statistical translation models as they were introduced by Brown et al. (1993) in their groundbreaking work The Mathematics of Statistical Machine Translation: Parameter Estimation. We concentrate on a simplified description of the first two translation models known as IBM Model 1 and 2. It is one major aim of this work to serve as tutoring material for students of computational linguistics, mathematics or computer science and therefore a lot of comments, additional examples and step-by-step explanations are given, augmenting the original formula by Brown et al. (1993). For both discussed models the calculations for a small parallel corpus are described in detail. 
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