Data selection and calibration issues in automatic language recognition- investigation with BUT-AGNITIO NIST LRE 2009 system

摘要

This paper summarizes the BUT-AGNITIO system for NIST Language Recognition Evaluation 2009. The post-evaluation analysis aimed mainly at improving the quality of the data (fixing language label problems and detecting overlapping speakers in the training and development sets) and investigation of different compositions of the development set. The paper further investigates into JFA-based acoustic system and reports results for new SVM-PCA systems going beyond BUT-Agnitio original NIST LRE 2009 submission. All results are presented on evaluation data from NIST LRE 2009 task.