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2019 NIST Speaker Recognition Evaluation Test Set -- CTS Challenge

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DataCite Commons2025-05-28 更新2026-05-06 收录
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https://datasets.lib.berkeley.edu/citation?persistentId=doi:10.60503/D3/ILFG9M
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2019 NIST Speaker Recognition Evaluation Test Set -- CTS Challenge was developed by the Linguistic Data Consortium (LDC) and NIST (National Institute of Standards and Technology). It contains approximately 635 hours of Tunisian Arabic telephone recordings for development and test, answer keys, enrollment, trial files and documentation from the CTS Challenge portion of the NIST-sponsored 2019 Speaker Recognition Evaluation (SRE). The ongoing series of SRE yearly evaluations conducted by NIST are intended to be of interest to researchers working on the general problem of text independent speaker recognition. To this end the evaluations are designed to be simple, to focus on core technology issues, to be fully supported and to be accessible to those wishing to participate. The 2019 evaluation task was speaker detection, that is, to determine whether a specified target speaker was speaking during a segment of speech. The evaluation was conducted in two parts: (1) a leaderboard-style challenge based on conversational telephone speech from LDC's Call My Net 2 (CMN2) corpus; and (2) a separate evaluation using audio-visual material collected by LDC for the VAST (Video Annotation for Speech Technology) project. Further information about the evaluation is contained in the evaluation plan included in this release.
提供机构:
UC Berkeley Library Dataverse
创建时间:
2025-05-28
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