Results of The 2015 NIST Language Recognition Evaluation

Hui Zhao, Désiré Bansé, George Doddington, Craig Greenberg, Jaime Hernández-Cordero, John Howard, Lisa Mason, Alvin Martin, Douglas Reynolds, Elliot Singer, Audrey Tong

In 2015, NIST conducted the most recent in an ongoing series of Language Recognition Evaluations (LRE) meant to foster research in language recognition. The 2015 Language Recognition Evaluation featured 20 target languages grouped into 6 language clusters. The evaluation was focused on distinguishing languages within each cluster, without disclosing which cluster a test language belongs to.

The 2015 evaluation introduced several new aspects, such as using limited and specified training data and a wider range of durations for test segments. Unlike in past LRE’s, systems were not required to output hard decisions for each test language and test segment, instead systems were required to provide a vector of log likelihood ratios to indicate the likelihood a test segment matches a target language. A total of 24 research organizations participated in this four-month long evaluation and combined they submitted 167 systems to be evaluated. The evaluation results showed that top-performing systems exhibited similar performance and there were wide variations in performance based on language clusters and within cluster language pairs. Among the 6 clusters, the French cluster was the hardest to recognize, with near random performance, and the Slavic cluster was the easiest to recognize.

DOI: 10.21437/Interspeech.2016-169

Cite as

Zhao, H., Bansé, D., Doddington, G., Greenberg, C., Hernández-Cordero, J., Howard, J., Mason, L., Martin, A., Reynolds, D., Singer, E., Tong, A. (2016) Results of The 2015 NIST Language Recognition Evaluation. Proc. Interspeech 2016, 3206-3210.

author={Hui Zhao and Désiré Bansé and George Doddington and Craig Greenberg and Jaime Hernández-Cordero and John Howard and Lisa Mason and Alvin Martin and Douglas Reynolds and Elliot Singer and Audrey Tong},
title={Results of The 2015 NIST Language Recognition Evaluation},
booktitle={Interspeech 2016},