Quality Estimation for Machine Translation Intro Acknowledgments Introduction Quality Estimation for MT at Subsentence Level Introduction Applications Labels Features Word Level Features Phrase Level Features Architectures Non Sequential Approaches Sequential Approaches APE Based Approaches Evaluation State of the Art Results The Predictor Estimator Approach Unbabels Hybrid Approach The APE Based Approach Quality Estimation for MT at Sentence Level Introduction Applications Labels Features Complexity Features Fluency Features Confidence Features Adequacy Features Pseudo Reference and Back Translation Features Linguistically Motivated Features Architectures Evaluation State of the Art Results Quality Estimation for MT at Document Level Introduction Applications Labels Labels for Evaluating Gisting Labels for Measuring Post Editing Effort Features Complexity Features Fluency Features Adequacy Features Discourse Aware Features Word Embedding Features Consensus and Pseudo Reference Features Architectures Evaluation State of the Art Results Referential Translation Machines Document Embeddings Best Post Editing Effort and Gisting Systems Quality Estimation for other Applications Text Simplification Applications Labels Features Architectures Evaluation State of the Art Results Automatic Text Summarization The Summary Assessment Approach The Summary Ranking Approach Grammatical Error Correction The ``Theres No Comparison Approach Fluency and Meaning Preservation Automatic Speech Recognition Natural Language Generation The QE Ranking Approach QE for Browse Pages Final Remarks Future Directions Resources and Toolkits Bibliography Authors Biographies Blank Page