CONF Soldo_ICASSP_2011/IDIAP Posterior Features for Template-based ASR Soldo, Serena Magimai-Doss, Mathew Pinto, Joel Praveen Bourlard, Hervé Posterior features speech recognition template-based approach EXTERNAL http://publications.idiap.ch/attachments/papers/2011/Soldo_ICASSP_2011.pdf PUBLIC Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing Prague, Czech Republic 2011 This paper investigates the use of phoneme class conditional probabilities as features (posterior features) for template-based ASR. Using 75 words and 600 words task-independent and speaker-independent setup on Phonebook database, we investigate the use of different posterior distribution estimators, different distance measures that are better suited for posterior distributions, and different training data. The reported experiments clearly demonstrate that posterior features are always superior, and generalize better than other classical acoustic features (at the cost of training a posterior distribution estimator).