Russian Stress Prediction using Maximum Entropy Ranking
Keith Hall, Richard Sproat · 2013
We explore a model of stress prediction in Russian using a combination of local contextual features and linguisticallymotivated features associated with the word's stem and suffix.We frame this as a ranking problem, where the objective is to rank the pronunciation with the correct stress above those with incorrect stress.We train our models using a simple Maximum Entropy ranking framework allowing for efficient prediction.An empirical evaluation shows that a model combining the local contextual features and the linguistically-motivated non-local features performs best in identifying both primary and secondary stress.