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.

本文概述与分析了 2022 年美国国家标准与技术研究所进行的最新语言识别评估 (LRE22) 的系统表现，发现使用不同评估条件下 Oromo 和 Tigrinya 较容易识别，而 Xhosa 和 Zulu 则较为困难。此外，当语音时长增加时，系统性能显著提高，但随着时间的增加，性能提高的速度逐渐变慢。