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Towards Universal Paraphrastic Sentence Embeddings
John Wieting, Mohit Bansal, Kevin Gimpel +1
We consider the problem of learning general-purpose, paraphrastic sentence embeddings based on supervision from the Paraphrase Database (Ganitkevitch et al., 2013). We compare six…
Mapping Unseen Words to Task-Trained Embedding Spaces
Pranava Swaroop Madhyastha, Mohit Bansal, Kevin Gimpel +1
We consider the supervised training setting in which we learn task-specific word embeddings. We assume that we start with initial embeddings learned from unlabelled data and update…
Discriminative Segmental Cascades for Feature-Rich Phone Recognition
Hao Tang, Weiran Wang, Kevin Gimpel +1
Discriminative segmental models, such as segmental conditional random fields (SCRFs) and segmental structured support vector machines (SSVMs), have had success in speech recognitio…
From Paraphrase Database to Compositional Paraphrase Model and Back
John Wieting, Mohit Bansal, Kevin Gimpel +2
The Paraphrase Database (PPDB; Ganitkevitch et al., 2013) is an extensive semantic resource, consisting of a list of phrase pairs with (heuristic) confidence estimates. However, it…