Vietnamese Capitalization and Punctuation Recovery Models
This work addresses a pre-processing bottleneck for Vietnamese NLP applications, though it is incremental as it builds on existing joint learning approaches.
The authors tackled the problem of capitalization and punctuation recovery for Vietnamese text, a low-resource language, by creating a public dataset and proposing a joint model named JointCapPunc, which showed effectiveness compared to single models and previous joint learning models.
Despite the rise of recent performant methods in Automatic Speech Recognition (ASR), such methods do not ensure proper casing and punctuation for their outputs. This problem has a significant impact on the comprehension of both Natural Language Processing (NLP) algorithms and human to process. Capitalization and punctuation restoration is imperative in pre-processing pipelines for raw textual inputs. For low resource languages like Vietnamese, public datasets for this task are scarce. In this paper, we contribute a public dataset for capitalization and punctuation recovery for Vietnamese; and propose a joint model for both tasks named JointCapPunc. Experimental results on the Vietnamese dataset show the effectiveness of our joint model compare to single model and previous joint learning model. We publicly release our dataset and the implementation of our model at https://github.com/anhtunguyen98/JointCapPunc