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Finite-state transducers are models that are being used in different areas of pattern recognition and computational linguistics. One of these areas is machine translation, in which the approaches that are based on building models automatically from training examples are becoming more and more attractive. Finite-state transducers are very adequate for use in(More)
Current machine translation (MT) systems are still not perfect. In practice, the output from these systems needs to be edited to correct errors. A way of increasing the productivity of the whole translation process (MT plus human work) is to incorporate the human correction activities within the translation process itself, thereby shifting the MT paradigm(More)
Probabilistic finite-state machines are used today in a variety of areas in pattern recognition, or in fields to which pattern recognition is linked: computational linguistics, machine learning, time series analysis, circuit testing, computational biology, speech recognition, and machine translation are some of them. In Part I of this paper, we survey these(More)
Probabilistic finite-state machines are used today in a variety of areas in pattern recognition or in fields to which pattern recognition is linked. In part I of this paper, we surveyed these objects and studied their properties. In this part, we study the relations between probabilistic finite-state automata and other well-known devices that generate(More)
The interpretation of handwritten sentences is carried out using a holistic approach in which both text image recognition and the interpretation itself are tightly integrated. Conventional approaches follow a serial, first-recognition then-interpretation scheme which cannot adequately use semantic–pragmatic knowledge to recover from recognition errors.(More)
Obtaining high-quality machine translations is still a long way off. A post-editing phase is required to improve the output of a machine translation system. An alternative is the so called computer-assisted translation. In this framework, a human translator interacts with the system in order to obtain high-quality translations. A statistical phrase-based(More)
Given a set of strings, the problem of finding a string that minimises its distance to the set is directly related with problems frequently encountered in areas involving Pattern Recognition or Computational Biology. Based on the Levenshtein (or edit) distance, different definitions of distances between a string and a set of strings can be adopted. In(More)
The problem of cyclic sequence alignment is considered. Most existing optimal methods for comparing cyclic sequences are very time consuming. For applications where these alignments are intensively used, optimal methods are seldom a feasible choice. The alternative to an exact and costly solution is to use a close-to-optimal but cheaper approach. In(More)