IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical methods for speech recognition
Statistical methods for speech recognition
Optimal linguistic decoding is a difficult computational problem
Pattern Recognition Letters
Inference of Finite-State Transducers by Using Regular Grammars and Morphisms
ICGI '00 Proceedings of the 5th International Colloquium on Grammatical Inference: Algorithms and Applications
A systematic comparison of various statistical alignment models
Computational Linguistics
Finite-State Speech-to-Speech Translation
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
Stochastic Finite-State Models for Spoken Language MachineTranslation
Machine Translation
Probabilistic Finite-State Machines-Part II
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic Finite-State Machines-Part I
IEEE Transactions on Pattern Analysis and Machine Intelligence
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
A finite-state approach to machine translation
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Machine Translation with Inferred Stochastic Finite-State Transducers
Computational Linguistics
A weighted finite state transducer translation template model for statistical machine translation
Natural Language Engineering
Linguistic knowledge in statistical phrase-based word alignment
Natural Language Engineering
Learning finite-state models for machine translation
Machine Learning
Clause restructuring for statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Improving statistical MT through morphological analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Automatic evaluation of machine translation quality using n-gram co-occurrence statistics
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Transfer-Based MT from Spanish into Basque: Reusability, Standardization and Open Source
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
Towards the improvement of statistical translation models using linguistic features
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
A specialized on-the-fly algorithm for lexicon and language model composition
IEEE Transactions on Audio, Speech, and Language Processing
GREAT: open source software for statistical machine translation
Machine Translation
Stochastic K-TSS bi-languages for machine translation
FSMNLP '11 Proceedings of the 9th International Workshop on Finite State Methods and Natural Language Processing
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The goal of this work is to develop a text and speech translation system from Spanish to Basque. This pair of languages shows quite odd characteristics as they differ extraordinarily in both morphology and syntax, thus, attractive challenges in machine translation are involved. Nevertheless, since both languages share official status in the Basque Country, the underlying motivation is not only academic but also practical. Finite-state transducers were adopted as basic translation models. The main contribution of this work involves the study of several techniques to improve probabilistic finite-state transducers by means of additional linguistic knowledge. Two methods to cope with both linguistics and statistics were proposed. The first one performed a morphological analysis in an attempt to benefit from atomic meaningful units when it comes to rendering the meaning from one language to the other. The second approach aimed at clustering words according to their syntactic role and used such phrases as translation unit. From the latter approach phrase-based finite-state transducers arose as a natural extension of classical ones. The models were assessed under a restricted domain task, very repetitive and with a small vocabulary. Experimental results shown that both morphological and syntactical approaches outperformed the baseline under different test sets and architectures for speech translation.