A reproduction of Apple's bi-directional LSTM models for language identification in short strings
Aarhus University（奥胡斯大学）；Information Sciences Institute（信息科学研究所）
英文摘要：
Language Identification is the task of identifying a document's language. For applications like automatic spell checker selection, language identification must use very short strings such as text message fragments. In this work, we reproduce a language identification architecture that Apple briefly sketched in a blog post. We confirm the bi-LSTM model's performance and find that it outperforms current open-source language identifiers. We further find that its language identification mistakes are due to confusion between related languages.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
