计算机科学
自然语言处理
人工智能
语言学
样品(材料)
书写系统
可靠性(半导体)
考试(生物学)
古生物学
哲学
化学
功率(物理)
物理
色谱法
量子力学
生物
标识
DOI:10.1075/ijcl.15.4.02lu
摘要
We describe a computational system for automatic analysis of syntactic complexity in second language writing using fourteen different measures that have been explored or proposed in studies of second language development. The system takes a written language sample as input and produces fourteen indices of syntactic complexity of the sample based on these measures. The system is designed with advanced second language proficiency research in mind, and is therefore developed and evaluated using college-level second language writing data from the Written English Corpus of Chinese Learners (Wen et al. 2005). Experimental results show that the system achieves very high reliability on unseen test data from the corpus. We illustrate how the system is used in an example application to investigate whether and to what extent each of these measures significantly differentiate between different proficiency levels
科研通智能强力驱动
Strongly Powered by AbleSci AI