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2022 NIST Language Recognition Evaluation Test and Development Sets

Listed in UC Berkeley Library Dataverse

2022 NIST Language Recognition Evaluation Test and Development Sets was developed by the Linguistic Data Consortium (LDC) and the National Institute of Standards and Technology (NIST).

Description

This release contains the test and development data, metadata, answer keys, and documentation for the 2022 NIST Language Recognition Evaluation (LRE22). The source speech data is comprised of approximately 222 hours of conversational telephone speech (CTS) and broadcast narrowband speech (BNBS) in 14 languages: Afrikaans, Tunisian Arabic, Algerian Arabic, Libyan Arabic, South African English, Indian-accented South African English, North African French, Ndebele, Oromo, Tigrinya, Tsonga, Venda, Xhosa and Zulu.

The goals of NIST's Language Recognition Evaluation are to advance language recognition technologies, to facilitate technology development, and to measure the performance of current state-of-the-art technology. LRE22 emphasized language recognition for African languages, including low resource languages, and expanded the range of test segment durations. Further information about the 2022 evaluation can be found in the 2022 NIST Language Recognition Evaluation Plan.

Links

Where it is published

Catalogue records · 1

Topics

Stated by source
Social Sciences
From keywords
Social Science
Inferred from text
Audio 65%
Provenance · 1 source records, 9 field assertions
SourceKeyLast seenRaw
UC Berkeley Library Dataversedoi:10.60503/D3/CQIMYN4 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[modality].local:modality:audioenrichment · datasets lib berkeley edukeyword-concept-rules@1.0.0title+description (65%)
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