Unsupervised Controllable Text Formalization
Channel: IBM Research
Date: 2019-06-20

By: Abhijit Mishra, IBM Research
Bio: Bio: 
Abhijit is currently a part of IBM Research, Bangalore, India, serving as Research Scientist in the department of AI Tech. Prior to joining IBM Research, He was a Ph.D. scholar in the Department of Computer Science and Engineering (CSE), IIT Bombay, working under the guidance of Prof. Pushpak Bhattacharyya.

AAAI 2019 Paper - https://arxiv.org/abs/1809.04556

Abstract:
We propose a novel framework for controllable natural language transformation. Realizing that the requirement of parallel corpus is practically unsustainable for controllable generation tasks, an unsupervised training scheme is introduced. The crux of the framework is a deep neural encoder-decoder that is reinforced with text-transformation knowledge through auxiliary modules (called scorers). The scorers, based on off-the-shelf language processing tools, decide the learning scheme of the encoder-decoder based on its actions. We apply this framework for the text-transformation task of formalizing an input text by improving its readability grade; the degree of required formalization can be controlled by the user at run-time. Experiments on public datasets demonstrate the efficacy of our model towards: (a) transforming a given text to a more formal style, and (b) introducing appropriate amount of formalness in the output text pertaining to the input control. Our code and datasets are released for academic use.