From Pivots to Graphs: Augmented CycleDensity as a Generalization to One Time InverseConsultation
This work addresses translation generation for resource-poor languages using minimal data, but it is incremental as it builds on existing methods.
The paper tackles the problem of generating translations using only raw bilingual dictionaries, proposing Augmented Cycle Density (ACD) as a framework that combines Cycle Density and One Time Inverse Consultation. The results show that ACD achieves more than double the coverage (74%) of OTIC with almost the same precision (76%) across three unseen language pairs.
This paper describes an approach used to generate new translations using raw bilingual dictionaries as part of the 4th Task Inference Across Dictionaries (TIAD 2021) shared task. We propose Augmented Cycle Density (ACD) as a framework that combines insights from two state of the art methods that require no sense information and parallel corpora: Cycle Density (CD) and One Time Inverse Consultation (OTIC). The task results show that across 3 unseen language pairs, ACD's predictions, has more than double (74%) the coverage of OTIC at almost the same precision (76%). ACD combines CD's scalability - leveraging rich multilingual graphs for better predictions, and OTIC's data efficiency - producing good results with the minimum possible resource of one pivot language.