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Neural Speech Translation using Lattice Transformations and Graph Networks

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Figure

Figure 1: Proposed lattice transformations. From topto bottom: 1) Original lattice with scores removed;2) Line graph transformation; 3) Subword segmenta-tion; 4) Lattice minimisation; 5) Addition of reverseand self-loop edges.
Figure 2: Model architecture, using the final Spanish lattice from Figure 1 and its corresponding English translationas an example.
Table 2: Results with transcriptions, in BLEU scores.“L+S+M” corresponds to the same results in Table 1and “L+S+M+T” is the setting with gold transcriptionsadded to the training set.

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