Understanding Tieq Viet with Deep Learning Models

Nguyen Ha Thanh

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arXiv · 2207.00975

Understanding Tieq Viet with Deep Learning Models

Nguyen Ha Thanh

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Abstract

Deep learning is a powerful approach in recovering lost information as well as harder inverse function computation problems. When applied in natural language processing, this approach is essentially making use of context as a mean to recover information through likelihood maximization. Not long ago, a linguistic study called Tieq Viet was controversial among both researchers and society. We find this a great example to demonstrate the ability of deep learning models to recover lost information. In the proposal of Tieq Viet, some consonants in the standard Vietnamese are replaced. A sentence written in this proposal can be interpreted into multiple sentences in the standard version, with different meanings. The hypothesis that we want to test is whether a deep learning model can recover the lost information if we translate the text from Vietnamese to Tieq Viet.

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BibTeX RIS

Nguyen Ha Thanh. 2022-07-03. Understanding Tieq Viet with Deep Learning Models. https://arxiv.org/abs/2207.00975

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