English

The 2022 NIST Language Recognition Evaluation

Computation and Language 2023-03-01 v1 Machine Learning Sound Audio and Speech Processing

Abstract

In 2022, the U.S. National Institute of Standards and Technology (NIST) conducted the latest Language Recognition Evaluation (LRE) in an ongoing series administered by NIST since 1996 to foster research in language recognition and to measure state-of-the-art technology. Similar to previous LREs, LRE22 focused on conversational telephone speech (CTS) and broadcast narrowband speech (BNBS) data. LRE22 also introduced new evaluation features, such as an emphasis on African languages, including low resource languages, and a test set consisting of segments containing between 3s and 35s of speech randomly sampled and extracted from longer recordings. A total of 21 research organizations, forming 16 teams, participated in this 3-month long evaluation and made a total of 65 valid system submissions to be evaluated. This paper presents an overview of LRE22 and an analysis of system performance over different evaluation conditions. The evaluation results suggest that Oromo and Tigrinya are easier to detect while Xhosa and Zulu are more challenging. A greater confusability is seen for some language pairs. When speech duration increased, system performance significantly increased up to a certain duration, and then a diminishing return on system performance is observed afterward.

Cite

@article{arxiv.2302.14624,
  title  = {The 2022 NIST Language Recognition Evaluation},
  author = {Yooyoung Lee and Craig Greenberg and Eliot Godard and Asad A. Butt and Elliot Singer and Trang Nguyen and Lisa Mason and Douglas Reynolds},
  journal= {arXiv preprint arXiv:2302.14624},
  year   = {2023}
}

Comments

5 pages, 10 figures

R2 v1 2026-06-28T08:51:54.627Z