Implementation and evaluation of a German HMM for POS disambiguation
Helmut Feldweg (University of Tuebingen)
TL;DR
This paper presents a German HMM-based POS tagger, compares its performance with other taggers, analyzes ambiguity resolution, and discusses unique disambiguation challenges for German.
Contribution
It introduces a German HMM model for POS tagging, compares it with other models, and provides detailed analysis of disambiguation types specific to German.
Findings
Performance comparable to English and French models
Identified unique disambiguation challenges for German
Analyzed error types and ambiguity resolution
Abstract
A German language model for the Xerox HMM tagger is presented. This model's performance is compared with two other German taggers with partial parameter re-estimation and full adaption of parameters from pre-tagged corpora. The ambiguity types resolved by this model are analysed and compared to ambiguity types of English and French. Finally, the model's error types are described. I argue that although the overall performance of these models for German is comparable to results for English and French, a more exact analysis demonstrates important differences in the types of disambiguation involved for German.
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Taxonomy
TopicsNatural Language Processing Techniques · Topic Modeling · Speech and dialogue systems