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}
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