← Back to papers
2018 CONLL CoNLL 2018

Sequence to Sequence Mixture Model for Diverse Machine Translation

🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — translation diversity
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Xuanli He , Gholamreza Haffari , Mohammad Norouzi

Topics

Machine Learning > Core Methods > Clustering Natural Language Processing > Applications > Machine Translation Natural Language Processing > Generation > Machine Translation Deep Learning > Models > Neural Networks

Keywords

machine translation mixture model beam search sequence-to-sequence model sequence to sequence translation diversity diversity generation
Download PDF

Related papers

A Unified Neural Network Model for Geolocating Twitter Users 2018
Latent Entities Extraction: How to Extract Entities that Do Not Appear in the Text? 2018
Uncovering Divergent Linguistic Information in Word Embeddings with Lessons for Intrinsic and Extrinsic Evaluation 2018
Predefined Sparseness in Recurrent Sequence Models 2018
Upcycle Your OCR: Reusing OCRs for Post-OCR Text Correction in Romanised Sanskrit 2018