Search Results for author: Shruti Rijhwani

Found 21 papers, 10 papers with code

Lexically Aware Semi-Supervised Learning for OCR Post-Correction

1 code implementation4 Nov 2021 Shruti Rijhwani, Daisy Rosenblum, Antonios Anastasopoulos, Graham Neubig

In addition, to enforce consistency in the recognized vocabulary, we introduce a lexically-aware decoding method that augments the neural post-correction model with a count-based language model constructed from the recognized texts, implemented using weighted finite-state automata (WFSA) for efficient and effective decoding.

Language Modelling Optical Character Recognition

Dependency Induction Through the Lens of Visual Perception

1 code implementation CoNLL (EMNLP) 2021 Ruisi Su, Shruti Rijhwani, Hao Zhu, Junxian He, Xinyu Wang, Yonatan Bisk, Graham Neubig

Our experiments find that concreteness is a strong indicator for learning dependency grammars, improving the direct attachment score (DAS) by over 50\% as compared to state-of-the-art models trained on pure text.

Constituency Grammar Induction Dependency Parsing

OCR Post Correction for Endangered Language Texts

1 code implementation EMNLP 2020 Shruti Rijhwani, Antonios Anastasopoulos, Graham Neubig

There is little to no data available to build natural language processing models for most endangered languages.

Optical Character Recognition

Temporally-Informed Analysis of Named Entity Recognition

no code implementations ACL 2020 Shruti Rijhwani, Daniel Preotiuc-Pietro

Natural language processing models often have to make predictions on text data that evolves over time as a result of changes in language use or the information described in the text.

Named Entity Recognition

Soft Gazetteers for Low-Resource Named Entity Recognition

1 code implementation ACL 2020 Shruti Rijhwani, Shuyan Zhou, Graham Neubig, Jaime Carbonell

However, designing such features for low-resource languages is challenging, because exhaustive entity gazetteers do not exist in these languages.

Cross-Lingual Entity Linking Entity Linking +2

Practical Comparable Data Collection for Low-Resource Languages via Images

1 code implementation24 Apr 2020 Aman Madaan, Shruti Rijhwani, Antonios Anastasopoulos, Yiming Yang, Graham Neubig

We propose a method of curating high-quality comparable training data for low-resource languages with monolingual annotators.

Machine Translation Translation

AlloVera: A Multilingual Allophone Database

no code implementations LREC 2020 David R. Mortensen, Xinjian Li, Patrick Littell, Alexis Michaud, Shruti Rijhwani, Antonios Anastasopoulos, Alan W. black, Florian Metze, Graham Neubig

While phonemic representations are language specific, phonetic representations (stated in terms of (allo)phones) are much closer to a universal (language-independent) transcription.

Speech Recognition

Towards Zero-resource Cross-lingual Entity Linking

1 code implementation WS 2019 Shuyan Zhou, Shruti Rijhwani, Graham Neubig

Cross-lingual entity linking (XEL) grounds named entities in a source language to an English Knowledge Base (KB), such as Wikipedia.

Cross-Lingual Entity Linking Entity Linking

Choosing Transfer Languages for Cross-Lingual Learning

1 code implementation ACL 2019 Yu-Hsiang Lin, Chian-Yu Chen, Jean Lee, Zirui Li, Yuyan Zhang, Mengzhou Xia, Shruti Rijhwani, Junxian He, Zhisong Zhang, Xuezhe Ma, Antonios Anastasopoulos, Patrick Littell, Graham Neubig

Cross-lingual transfer, where a high-resource transfer language is used to improve the accuracy of a low-resource task language, is now an invaluable tool for improving performance of natural language processing (NLP) on low-resource languages.

Cross-Lingual Transfer

The ARIEL-CMU Systems for LoReHLT18

no code implementations24 Feb 2019 Aditi Chaudhary, Siddharth Dalmia, Junjie Hu, Xinjian Li, Austin Matthews, Aldrian Obaja Muis, Naoki Otani, Shruti Rijhwani, Zaid Sheikh, Nidhi Vyas, Xinyi Wang, Jiateng Xie, Ruochen Xu, Chunting Zhou, Peter J. Jansen, Yiming Yang, Lori Levin, Florian Metze, Teruko Mitamura, David R. Mortensen, Graham Neubig, Eduard Hovy, Alan W. black, Jaime Carbonell, Graham V. Horwood, Shabnam Tafreshi, Mona Diab, Efsun S. Kayi, Noura Farra, Kathleen McKeown

This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery and Linking (EDL), and detection of Situation Frames in Text and Speech (SF Text and Speech).

Machine Translation Translation

Zero-shot Neural Transfer for Cross-lingual Entity Linking

1 code implementation9 Nov 2018 Shruti Rijhwani, Jiateng Xie, Graham Neubig, Jaime Carbonell

To address this problem, we investigate zero-shot cross-lingual entity linking, in which we assume no bilingual lexical resources are available in the source low-resource language.

Cross-Lingual Entity Linking Entity Linking

Estimating Code-Switching on Twitter with a Novel Generalized Word-Level Language Detection Technique

no code implementations ACL 2017 Shruti Rijhwani, Royal Sequiera, Monojit Choudhury, Kalika Bali, Ch Maddila, ra Shekhar

Word-level language detection is necessary for analyzing code-switched text, where multiple languages could be mixed within a sentence.

Preserving Intermediate Objectives: One Simple Trick to Improve Learning for Hierarchical Models

no code implementations23 Jun 2017 Abhilasha Ravichander, Shruti Rijhwani, Rajat Kulshreshtha, Chirag Nagpal, Tadas Baltrušaitis, Louis-Philippe Morency

In this work, we focus on improving learning for such hierarchical models and demonstrate our method on the task of speaker trait prediction.

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