2019 NIST Speaker Recognition Evaluation Test Set -- CTS Challenge

Introduction

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 Ev….

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.

Data

The telephone speech data for the CTS Challenge was drawn from the CMN2 collection conducted by LDC in Tunisia in which Tunisian Arabic speakers called friends or relatives who agreed to record their telephone conversations lasting between 8-10 minutes. The speech segments include PSTN (public switched telephone network) and VOIP (voice over IP) data. This telephone speech is presented in sphere format as 8-bit a-law with a sample rate of 8000 KHz.

Samples

Please see the following audio sample.

Updates

None at this time.