Automatic Spelling Correction for Resource-Scarce Languages using Deep Learning – 第2页 – NLPIR自然语言处理与信息检索共享平台

自然语言处理与信息检索共享平台 自然语言处理与信息检索共享平台

Automatic Spelling Correction for Resource-Scarce Languages using Deep Learning

NLPIR SEMINAR 34th ISSUE COMPLETED

Last Monday, Changhe Li gave a presentation about the paper, Zhaoyang Wang introduced his research work.

The paper proposed a character based Sequence-to-sequence text Correction Model for Indic Languages (SCMIL). The encoder and decoder both use LSTM. A dataset for Hindi and Telugu spelling errors is published on Github.

The method is not complex and the model’s performance is not that good nowadays.

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