Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary ...

Computer Science > Computation and Language arXiv:1804.08205 (cs) [Submitted on 23 Apr 2018 (v1), last revised 25 Feb 2020 (this version, v4)] Title:Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model Authors:Sabrina J. Mielke, Jason Eisner View a PDF of the paper titled Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model, by Sabrina J. Mielke and Jason Eisner View PDF

Abstract:We show how the spellings of known words can help us deal with unknown words in open-vocabulary NLP tasks. The method we propose can be used to extend any closed-vocabulary generative model, but in this paper we specifically consider the case of neural language modeling. Our Bayesian generative story combines a standard RNN language model (generating the word tokens in each sentence) with an RNN-based spelling model (generating the letters in each word type). These two RNNs respectively capture sentence structure and word structure, and are kept separate as in linguistics. By invoking the second RNN to generate spellings for novel words in context, we obtain an open-vocabulary language model. For known words, embeddings are naturally inferred by combining evidence from type spelling and token context. Comparing to baselines (including a novel strong baseline), we beat previous work and establish state-of-the-art results on multiple datasets.

Comments:	Accepted for publication at AAAI 2019
Subjects:	Computation and Language (cs.CL)
Cite as:	arXiv:1804.08205 [cs.CL]
(or arXiv:1804.08205v4 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.1804.08205 Focus to learn more arXiv-issued DOI via DataCite

Submission history

From: Sabrina Mielke [view email] [v1] Mon, 23 Apr 2018 00:56:23 UTC (56 KB) [v2] Thu, 6 Sep 2018 18:26:20 UTC (46 KB) [v3] Fri, 23 Nov 2018 21:52:46 UTC (48 KB) [v4] Tue, 25 Feb 2020 18:27:08 UTC (48 KB) Full-text links:

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