Morpho Challenge

The objective of the Morpho Challenge is to design a statistical machine learning algorithm that discovers which morphemes (smallest individually meaningful units of language) words consist of. Ideally, these are basic vocabulary units suitable for different tasks, such as text understanding, machine translation, information retrieval, and statistical language modeling.

Morpho Challenges and workshops

Complete results 2007-2010

Information retrieval (IR) and statistical machine translation (SMT) evaluations correspond to those of Challenge 2010. All older submissions have been re-evaluated.

Descriptions of the evaluations and the evaluated algorithms are found in the following article:

(Click on the title for suggested BibTeX entry.)

Evaluation methods & software

The MC evaluation scripts are implemented in Perl. EMMA, EMMA-2, CoMMA, and BPR are implemented in Python. In addition, EMMA and EMMA-2 require the lpsolve library and CoMMA and BPR require the Munkres module for Python.