论文标题
探索和调整中国GPT到拼音输入方法
Exploring and Adapting Chinese GPT to Pinyin Input Method
论文作者
论文摘要
虽然GPT已成为文本生成任务的事实上的方法，但其应用于拼音输入方法仍未探索。在这项工作中，我们进行了首次探索，以利用中国GPT进行拼音输入方法。我们发现，冻结的GPT在完美的拼音上取得了最先进的性能。但是，当输入包括缩写的拼音时，性能会大大降低。原因是缩写的拼音可以映射到许多完美的拼音，这与更多的汉字链接在一起。我们通过两种策略来缓解这个问题，包括用拼音丰富上下文并优化训练过程以帮助区分同音词。为了进一步促进Pinyin输入方法的评估，我们创建了一个由15个域的270K实例组成的数据集。结果表明，我们的方法改善了所有域中缩写的菠萝的性能。模型分析表明，这两种策略都有助于提高性能。
While GPT has become the de-facto method for text generation tasks, its application to pinyin input method remains unexplored. In this work, we make the first exploration to leverage Chinese GPT for pinyin input method. We find that a frozen GPT achieves state-of-the-art performance on perfect pinyin. However, the performance drops dramatically when the input includes abbreviated pinyin. A reason is that an abbreviated pinyin can be mapped to many perfect pinyin, which links to even larger number of Chinese characters. We mitigate this issue with two strategies, including enriching the context with pinyin and optimizing the training process to help distinguish homophones. To further facilitate the evaluation of pinyin input method, we create a dataset consisting of 270K instances from 15 domains. Results show that our approach improves performance on abbreviated pinyin across all domains. Model analysis demonstrates that both strategies contribute to the performance boost.
