M.S. Thesis Defense: Wenyan Li

Monday, June 25, 2018
2:00 p.m.-4:00 p.m.
AVW 2460
Maria Hoo
301 405 3681
mch@umd.edu

ANNOUNCEMENT:  M.S. Thesis Defense


Name: Wenyan Li

 

Committee: 

Professor Betash Babadi, Chair

Professor Jordan Boyd-Graber

Professor Alexander Barg

 

Date & Time: Monday, June 25th, 2018 at 2:00pm

 

Place: AVW 2460 

 

Title: Incremental Prediction of Sentence-final Verbs with Attentive Recurrent Neural Networks 

Abstract: Sentence-final verb prediction has garnered attention both in computational linguistics and psycholinguistics. It is indispensable for understanding human processing of verb-final languages, more recently, it has been used for computational approaches to simultaneous interpretation from verb-final to verb-medial languages. While previous approaches use classical statistical models, we introduce an attention-based neural model, Attentive Neural Verb Inference for Incremental Language (ANVIIL), to incrementally predict final verbs on incomplete sentences. Our approach both better predicts the final verbs in Japanese and German and provides more interpretable explanations of why those verbs are selected.



Audience: Faculty 

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