Advanced Language Recognition using Cepstra and Phonotactics: MITLL System Performance on the NIST 2005 Language Recognition Evaluation

This paper presents a description of the MIT Lincol n Laboratory submissions to the 2005 NIST Language Recognition Evaluation (LRE05). As was true in 2003, the 2005 submissions were combinations of core cepstral and phonotactic recognizers whose outputs were fused to generate final scores. For the 2005 evaluation, Lin coln Laboratory had five submissions built upon fused combinations of six core systems. Major improvements included the generation of phone streams using latt ices, SVM-based language models using lattice-derived phonotactics, and binary tree language models. In a ddition, a development corpus was assembled that was designed to test robustness to unseen languages and sources. La nguage recognition trends based on NIST evaluations conducted since 1996 show a steady improvement in language recognition performance.