Introduction 2019 NIST Speaker Recognition Evaluation Test Set -- Audio-Visual (LDC2023V01) was developed by the Linguistic Data Consortium (LDC) and NIST (National Institute of Standards and Technology). It contains approximately 64 hours of English audio-visual data for development and test, answer keys, enrollment, trial files and documentation from 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 corpus; and (2) a separate evaluation using audio-visual data collected by LDC for the VAST (Video Annotation for Speech Technology) project. Further information about the 2019 evaluation is contained in the evaluation plan included in this release. Data The VAST collection focused on amateur video recordings from various online media hosting services. The recordings vary in duration from 17.5 seconds to 13 minutes. Videos are encoded/compressed as mp4 files. Audio tracks are in aac format with a sample rate of 44.1 KHz; most have two audio channels (stereo), but some are monophonic (one channel).

Creator(s)

Omid Sadjadi

Craig Greenberg

Xuansong Li

Stephanie Strassel

Distributor(s)

Linguistic Data Consortium

Right Holder(s)

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