REPORT Soldo_Idiap-RR-17-2012/IDIAP Integrating Posterior Features and Self-Organizing Maps for Isolated Word Recognition without Dynamic Programming Soldo, Serena Magimai-Doss, Mathew fixed-size word patterns isolated word recognition Posterior features Self-Organizing Maps EXTERNAL http://publications.idiap.ch/attachments/reports/2012/Soldo_Idiap-RR-17-2012.pdf PUBLIC Idiap-RR-17-2012 2012 Idiap June 2012 In recent works, the use of phone class-conditional posterior probabilities (posterior features) directly as features provided successful results in template-based ASR systems. Moreover, it has been shown that these features tend to be sparse and orthogonal. Given such properties, new types of ASR may be investigated. In this work, we investigate the use of Self-Organizing Maps to transform sequences of posterior feature vectors representing words into sparse fixed-size patterns. We evaluate the ability of these patterns to discriminate between words in the context of template-based ASR using a simple histogram matching technique (i.e. without the use of dynamic programming). We present experiments on 75-word speaker- and task-independent isolated word recognition task.