Data selection and calibration issues in automatic language recognition - investigation with BUT-AGNITIO NIST LRE 2009 system.
ODYSSEY 2010: THE SPEAKER AND LANGUAGE RECOGNITION WORKSHOP(2010)
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.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络