Empirical Evaluation of Sequence-to-Sequence Models for Word Discovery in Low-resource Settings

29 Jun 2019Marcely Zanon BoitoAline VillavicencioLaurent Besacier

Since Bahdanau et al. [1] first introduced attention for neural machine translation, most sequence-to-sequence models made use of attention mechanisms [2, 3, 4]. While they produce soft-alignment matrices that could be interpreted as alignment between target and source languages, we lack metrics to quantify their quality, being unclear which approach produces the best alignments... (read more)

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