paper-with-me

홈 › Papers

Out-of-the-box Universal Romanization Tool uroman

2018-07-01 · ACL 2018 7 · Ulf Hermjakob, Jonathan May, Kevin Knight

We present uroman, a tool for converting text in myriads of languages and scripts such as Chinese, Arabic and Cyrillic into a common Latin-script representation. The tool relies on Unicode data and other tables, and handles nearly all character sets, including some that are quite obscure such as Tibetan and Tifinagh. uroman converts digital numbers in various scripts to Western Arabic numerals. Romanization enables the application of string-similarity metrics to texts from different scripts without the need and complexity of an intermediate phonetic representation. The tool is freely and publicly available as a Perl script suitable for inclusion in data processing pipelines and as an interactive demo web page.

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

Machine Translation

Similar Papers 제목 키워드 기반

Romanization-based Large-scale Adaptation of Multilingual Language Models

2023-04-18 · Sukannya Purkayastha, Sebastian Ruder, Jonas Pfeiffer, Iryna Gurevych 외

Large multilingual pretrained language models (mPLMs) have become the de facto state of the art for cross-lingual transfer in NLP. However, their large-scale deployment to many languages, besides pretraining data scarcit…

Cross-Lingual TransferTransliteration

On Romanization for Model Transfer Between Scripts in Neural Machine Translation

2020-09-30 · Findings of the Association for Computational Linguistics 2020 · Chantal Amrhein, Rico Sennrich

Transfer learning is a popular strategy to improve the quality of low-resource machine translation. For an optimal transfer of the embedding layer, the child and parent model should share a substantial part of the vocabu…

Machine TranslationTransfer LearningTranslation

On the Geometry and Optimization of Polynomial Convolutional Networks

2024-10-01 · Vahid Shahverdi, Giovanni Luca Marchetti, Kathlén Kohn

We study convolutional neural networks with monomial activation functions. Specifically, we prove that their parameterization map is regular and is an isomorphism almost everywhere, up to rescaling the filters. By levera…

Geometry of Polynomial Neural Networks

2024-02-01 · Kaie Kubjas, Jiayi Li, Maximilian Wiesmann

We study the expressivity and learning process for polynomial neural networks (PNNs) with monomial activation functions. The weights of the network parametrize the neuromanifold. In this paper, we study certain neuromani…

Polynomial Neural Networks

Algebraic Complexity and Neurovariety of Linear Convolutional Networks

2024-01-29 · Vahid Shahverdi

In this paper, we study linear convolutional networks with one-dimensional filters and arbitrary strides. The neuromanifold of such a network is a semialgebraic set, represented by a space of polynomials admitting specif…