论文标题
迈向大型数据挖掘，以进行数据驱动的标志语言分析
Towards Large-Scale Data Mining for Data-Driven Analysis of Sign Languages
论文作者
论文摘要
访问手语数据还远远不够。我们表明，通过应用数据过滤以执行质量标准并发现过滤数据中的模式，可以从Tiktok，Instagram和YouTube等社交网络服务（例如Tiktok，Instagram和YouTube）中收集数据，从而使分析和模型更易于分析和模型。使用我们的数据收集管道，我们收集并研究了美国手语（ASL）和巴西手语（天秤座）中对歌曲的解释。我们通过查看方向和位置语音参数的共依赖性来探索它们的差异和相似性
Access to sign language data is far from adequate. We show that it is possible to collect the data from social networking services such as TikTok, Instagram, and YouTube by applying data filtering to enforce quality standards and by discovering patterns in the filtered data, making it easier to analyse and model. Using our data collection pipeline, we collect and examine the interpretation of songs in both the American Sign Language (ASL) and the Brazilian Sign Language (Libras). We explore their differences and similarities by looking at the co-dependence of the orientation and location phonological parameters
