Machine translation using neural networks and finite-state models

Both Neural Networks and Finite-State Models have recently proved to be encouraging approaches to Example-Based Machine Translation. This paper compares the translation performances achieved with the two techniques as well as the corresponding resources required. To this end, both Elman Simple Recurrent Nets and Subsequential Transducers were trained to tackle a simple pseudo-natural machine translation task.

[1]  Jean Berstel,et al.  Transductions and context-free languages , 1979, Teubner Studienbücher : Informatik.

[2]  Andreas Stolcke.  Learning Feature-based Semantics with Simple Recurrent Networks , 1990 .

[3]  Ajay N. Jain,et al.  Parsing Complex Sentences with Structured Connectionist Networks , 1991, Neural Computation.

[4]  Alex Waibel,et al.  JANUS: a speech-to-speech translation system using connectionist and symbolic processing strategies , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[5]  Robert L. Mercer,et al.  The Mathematics of Statistical Machine Translation: Parameter Estimation , 1993, CL.

[6]  Enrique Vidal,et al.  Learning Subsequential Transducers for Pattern Recognition Interpretation Tasks , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  C. Lee Giles,et al.  Pruning recurrent neural networks for improved generalization performance , 1994, IEEE Trans. Neural Networks.

[8]  Enrique Vidal,et al.  Application of OSTIA to Machine Translation Tasks , 1994, ICGI.

[9]  Andreas Zell,et al.  SNNS (Stuttgart Neural Network Simulator) , 1994 .

[10]  Francisco Casacuberta,et al.  Preliminary experiments for automatic speech understanding through simple recurrent networks , 1995, EUROSPEECH.

[11]  Enrique Vidal,et al.  Learning language translation in limited domains using finite-state models: some extensions and improvements , 1995, EUROSPEECH.

[12]  Hermann Ney,et al.  HMM-Based Word Alignment in Statistical Translation , 1996, COLING.

[13]  Francisco Casacuberta,et al.  A connectionist approach to machine translation , 1997, EUROSPEECH.

[14]  Francisco Casacuberta,et al.  Error correcting parsing for text-to-text machine translation using finite state models , 1997, TMI.

[15]  Enrique Vidal,et al.  Finite-state speech-to-speech translation , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[16]  Enrique Vidal,et al.  Language understanding and subsequential transducer learning , 1993, Comput. Speech Lang..