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Found 7 papers, 2 papers with code
Neural Text Style Transfer via Denoising and Reranking
We introduce a simple method for text style transfer that frames style transfer as denoising: we synthesize a noisy corpus and treat the source style as a noisy version of the target style.
Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction
Translation-based methods for grammar correction that directly map noisy, ungrammatical text to their clean counterparts are able to correct a broad range of errors; however, such techniques are bottlenecked by the need for a large parallel corpus of noisy and clean sentence pairs.
Neural Text Generation: A Practical Guide
Deep learning methods have recently achieved great empirical success on machine translation, dialogue response generation, summarization, and other text generation tasks.
Data Noising as Smoothing in Neural Network Language Models
Data noising is an effective technique for regularizing neural network models.
Neural Language Correction with Character-Based Attention
Motivated by these issues, we present a neural network-based approach to language correction.
Building DNN Acoustic Models for Large Vocabulary Speech Recognition
We compare standard DNNs to convolutional networks, and present the first experiments using locally-connected, untied neural networks for acoustic modeling.
Ranked #11 on
Speech Recognition
on swb_hub_500 WER fullSWBCH
