New insight into the use of phone log-likelihood ratios as features for language recognition.

Phone Log-Likelihood Ratio (PLLR) features have been recently introduced as an effective way of making use of frame-level phone posteriors in language and speaker recognition systems. In this paper, a deep insight into PLLR features is made and further evidence of the usefulness of these features in spoken language recognition tasks is provided, with a new set of experiments carried out on the NIST 2007 LRE dataset, combining the latest progresses made in optimizing the features. PLLR features are projected into a subspace that enhances the information retrieved by the system. Then, dimensionality reduction is performed on the projected subspace by means of Principal Component Analysis, and shifted deltas are computed on the reduced features to optimize performance. Figures attained are among the best reported so far on the NIST 2007 LRE dataset.