Computer Science > Artificial Intelligence
[Submitted on 11 Nov 2018 (v1), last revised 6 Jun 2019 (this version, v4)]
Title:Open Vocabulary Learning for Neural Chinese Pinyin IME
View PDFAbstract:Pinyin-to-character (P2C) conversion is the core component of pinyin-based Chinese input method engine (IME). However, the conversion is seriously compromised by the ambiguities of Chinese characters corresponding to pinyin as well as the predefined fixed vocabularies. To alleviate such inconveniences, we propose a neural P2C conversion model augmented by an online updated vocabulary with a sampling mechanism to support open vocabulary learning during IME working. Our experiments show that the proposed method outperforms commercial IMEs and state-of-the-art traditional models on standard corpus and true inputting history dataset in terms of multiple metrics and thus the online updated vocabulary indeed helps our IME effectively follows user inputting behavior.
Submission history
From: Zhuosheng Zhang [view email][v1] Sun, 11 Nov 2018 05:07:25 UTC (1,144 KB)
[v2] Tue, 14 May 2019 13:02:18 UTC (1,421 KB)
[v3] Wed, 5 Jun 2019 07:11:16 UTC (2,843 KB)
[v4] Thu, 6 Jun 2019 12:54:31 UTC (2,843 KB)
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