| Challenge: | Stemma generation is a task where manuscripts are copied and copied from each other and from M. Existing methods to generate stemma using unweighted token similarity weighting have been used. |
| Approach: | They propose to use a distance model to weight the texts of M1 and M2 to estimate the most likely tree from a series of mapping processes. |
| Outcome: | The proposed method is small in the experimental scenario(s) it is based on psycholinguistically gained distance matrices of letters in three modalities: vision, audition and motorics. |
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