Unwritten Languages Demand Attention Too! Word Discovery with Encoder-Decoder Models
Table 2: Unsupervised Word Discovery results with 4,643 sentences.
['[EMPTY]', '[BOLD] TOKENS  [BOLD] Recall', '[BOLD] TOKENS  [BOLD] Precision', '[BOLD] TOKENS  [BOLD] F-score', '[BOLD] TYPES  [BOLD] Recall', '[BOLD] TYPES  [BOLD] Precision', '[BOLD] TYPES  [BOLD] F-score']
Moreover, we show that the proposed reverse model considerably improves type and token retrieval. This seems to confirm the hypothesis that reversing the alignment direction results in a better segmentation (because the attention model has to align each Mboshi symbol to French words with a total probability of 1).