Summary of the paper
| Title | Suffix Trees as Language Models |
|---|---|
| Authors | Casey Redd Kennington, Martin Kay and Annemarie Friedrich |
| Abstract | Suffix trees are data structures that can be used to index a corpus. In this paper, we explore how some properties of suffix trees naturally provide the functionality of an n-gram language model with variable n. We explain these properties of suffix trees, which we leverage for our Suffix Tree Language Model (STLM) implementation and explain how a suffix tree implicitly contains the data needed for n-gram language modeling. We also discuss the kinds of smoothing techniques appropriate to such a model. We then show that our suffix-tree language model implementation is competitive when compared to the state-of-the-art language model SRILM (Stolke, 2002) in statistical machine translation experiments. |
| Topics | Language modelling, Machine Translation, SpeechToSpeech Translation, Statistical and machine learning methods |
Full paper  |
Suffix Trees as Language Models |
| Bibtex | @InProceedings{KENNINGTON12.649, author = {Casey Redd Kennington and Martin Kay and Annemarie Friedrich}, title = {Suffix Trees as Language Models}, booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)}, year = {2012}, month = {may}, date = {23-25}, address = {Istanbul, Turkey}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-7-7}, language = {english} } |