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natural-language-processing-3

Bangla Spelling Error Correction

3260 papers • 126 benchmarks • 313 datasets

Bangla spell checker which improves the quality of suggestions for misspelled words.

(Image credit: Papersgraph)

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DPCSpell-Bangla-SEC-Corpus

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awslabs/sockeye

2 papers 1,210

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DPCSpell-Bangla-SEC-Corpus

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Most implemented papers

Neural Machine Translation by Jointly Learning to Align and Translate

Yoshua Bengio, Kyunghyun Cho, Dzmitry Bahdanau•Sun Aug 31 2014

It is conjecture that the use of a fixed-length vector is a bottleneck in improving the performance of this basic encoder-decoder architecture, and it is proposed to extend this by allowing a model to automatically (soft-)search for parts of a source sentence that are relevant to predicting a target word, without having to form these parts as a hard segment explicitly.

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Convolutional Sequence to Sequence Learning

Denis Yarats, Jonas Gehring, Michael Auli, David Grangier, Yann Dauphin•Sun May 07 2017

This work introduces an architecture based entirely on convolutional neural networks, which outperform the accuracy of the deep LSTM setup of Wu et al. (2016) on both WMT'14 English-German and WMT-French translation at an order of magnitude faster speed, both on GPU and CPU.

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DPCSpell: A Transformer-based Detector-Purificator-Corrector Framework for Spelling Error Correction of Bangla and Resource Scarce Indic Languages

Swakkhar Shatabda, Salekul Islam, Mehedi Hasan Bijoy, Nahid Hossain•Fri Dec 31 2021

A novel detector-purificator-corrector framework based on denoising transformers that outperforms previous state-of-the-art methods by a significant margin for Bangla spelling error correction and presents a method for large-scale corpus creation from scratch which in turn resolves the resource limitation problem of any left-to-right scripted language.

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Bangla Spelling Error Correction | State-of-the-Art