Synthetic Data for Neural Machine Translation of Spoken-Dialects

By Hany Hassan, Mostafa Elaraby, Ahmed Y. Tawfik. 2017

23 citations recorded by the source corpus.

Subfields: Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

1. Graham Neubig
2. Eduard H. Hovy
3. Soroush Vosoughi
4. Antonios Anastasopoulos
5. Varun Prashant Gangal
6. Teruko Mitamura
7. Jason Wei
8. Steven Y. Feng

Citations in the corpus

• A Survey of Data Augmentation Approaches for NLP (2021, methodology): “Mizumoto et al. (2011) DA by extracting Japanese GEC training data from the revision log of a language learning SNS. Hassan et al. (2017) Present a DA method to project words from closely-related high-resource languages to low-resource languages using word embedding representations.”
• Generalized Data Augmentation for Low-Resource Translation (2019, methodology): “Hassan et al. (2017) synthesized data with word embeddings for spoken dialect translation, with a process that requires a LRL - ENG as well as a HRL - LRL dictionary, while our work only uses a HRL - LRL dictionary.”