A statistical approach to machine translation
Computational Linguistics
String alignment with substitution, insertion, deletion, squashing, and expansion operations
Information Sciences—Informatics and Computer Science: An International Journal
An introduction to model selection
Journal of Mathematical Psychology
A linear space algorithm for computing maximal common subsequences
Communications of the ACM
Semiring frameworks and algorithms for shortest-distance problems
Journal of Automata, Languages and Combinatorics
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Improved statistical alignment models
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Joint-sequence models for grapheme-to-phoneme conversion
Speech Communication
Latent-variable modeling of string transductions with finite-state methods
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
SRWS '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
A re-examination of lexical association measures
MWE '09 Proceedings of the Workshop on Multiword Expressions: Identification, Interpretation, Disambiguation and Applications
Letter-phoneme alignment: an exploration
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
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We provide simple generalizations of the classical Needleman-Wunsch algorithm for aligning two sequences. First, we let both sequences be defined over arbitrary, potentially different alphabets. Secondly, we consider similarity functions between elements of both sequences with ranges in a semiring. Thirdly, instead of considering only 'match', 'mismatch' and 'skip' operations, we allow arbitrary non-negative alignment 'steps'S. Next, we present novel combinatorial formulas for the number of monotone alignments between two sequences for selected steps S. Finally, we illustrate sample applications in natural language processing that require larger steps than available in the original Needleman-Wunsch sequence alignment procedure such that our generalizations can be fruitfully adopted.