论文标题
Gboard中的空间模型个性化
Spatial model personalization in Gboard
论文作者
论文摘要
我们通过修改高斯空间模型来使用个性化的钥匙中心偏移量值，并且可以选择地，将虚拟键盘调整为单个用户行为，以适应个人用户行为。通过大量的实际研究，我们确定了训练数据数量和权重的重要性，以及避免过度拟合的钥匙的群集数量。虽然过去的研究表明了使用人工简化的虚拟键盘和游戏或固定打字提示的潜力，但我们使用高度调整的Gboard应用程序与代表性的用户及其真实的打字行为一起证明了有效性。在各种顶级语言中，我们在打字速度和解码器的准确性方面都取得了很小的改进。
We introduce a framework for adapting a virtual keyboard to individual user behavior by modifying a Gaussian spatial model to use personalized key center offset means and, optionally, learned covariances. Through numerous real-world studies, we determine the importance of training data quantity and weights, as well as the number of clusters into which to group keys to avoid overfitting. While past research has shown potential of this technique using artificially-simple virtual keyboards and games or fixed typing prompts, we demonstrate effectiveness using the highly-tuned Gboard app with a representative set of users and their real typing behaviors. Across a variety of top languages, we achieve small-but-significant improvements in both typing speed and decoder accuracy.
