Choosing an Optimal Architecture for Segmentation and POS-Tagging of Modern Hebrew

@inproceedings{BarHaim2005ChoosingAO,
  title={Choosing an Optimal Architecture for Segmentation and POS-Tagging of Modern Hebrew},
  author={Roy Bar-Haim and Khalil Sima'an and Yoad Winter},
  booktitle={SEMITIC@ACL},
  year={2005}
}
A major architectural decision in designing a disambiguation model for segmentation and Part-of-Speech (POS) tagging in Semitic languages concerns the choice of the input-output terminal symbols over which the probability distributions are defined. In this paper we develop a segmenter and a tagger for Hebrew based on Hidden Markov Models (HMMs). We start out from a morphological analyzer and a very small morphologically annotated corpus. We show that a model whose terminal symbols are word… CONTINUE READING

Tables, Results, and Topics from this paper.

Key Quantitative Results

  • Comparing our best architecture to the Segal tagger’s results under the same experimental setting shows an improvement of 1.5% in segmentation accuracy and 4.5% in tagging accuracy over Segal’s results.

Citations

Publications citing this paper.

References

Publications referenced by this paper.
SHOWING 1-10 OF 12 REFERENCES