2016 NIST Speaker Recognition Evaluation Test Set
| Item Name: | 2016 NIST Speaker Recognition Evaluation Test Set |
| Author(s): | Craig Greenberg, Omid Sadjadi, Timothee Kheyrkhah, Karen Jones, Kevin Walker, Stephanie Strassel, David Graff |
| LDC Catalog No.: | LDC2019S20 |
| ISBN: | 1-58563-904-4 |
| ISLRN: | 261-271-974-389-4 |
| DOI: | https://doi.org/10.35111/bd9y-k619 |
| Release Date: | October 15, 2019 |
| Member Year(s): | 2019 |
| DCMI Type(s): | Sound |
| Sample Type: | alaw |
| Sample Rate: | 8000 |
| Data Source(s): | telephone speech |
| Project(s): | NIST SRE |
| Application(s): | speaker identification |
| Language(s): | Tagalog, Yue Chinese, Cebuano, Mandarin Chinese |
| Language ID(s): | tgl, yue, ceb, cmn |
| License(s): |
LDC User Agreement for Non-Members |
| Online Documentation: | LDC2019S20 Documents |
| Licensing Instructions: | Subscription & Standard Members, and Non-Members |
| Citation: | Greenberg, Craig, et al. 2016 NIST Speaker Recognition Evaluation Test Set LDC2019S20. Web Download. Philadelphia: Linguistic Data Consortium, 2019. |
| Related Works: | View |
Introduction
2016 NIST Speaker Recognition Evaluation Test Set was developed by the Linguistic Data Consortium (LDC) and NIST (National Institute of Standards and Technology). It contains approximately 340 hours of short segments of Tagalog, Cantonese, Cebuano, and Mandarin telephone speech used as development and test data in the NIST-sponsored 2016 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 SRE task is speaker detection, that is, to determine whether a specified target speaker is speaking during a given segment of speech. As in previous evaluations, SRE16 focused on telephone speech recorded over a variety of handset types for the training and test conditions. Further information about the evaluation, including some features added in SRE16, is contained in the evaluation plan included in this release.
Data
The telephone speech data was drawn from the Call My Net 2015 Corpus collected by LDC. Native speakers of Tagalog, Cantonese, Cebuano, or Mandarin (220 unique speakers) made a total of 10 telephone calls each, talking to people within their existing social networks. Speakers were encouraged to use different telephone instruments in a variety of acoustic settings and were instructed to talk for 8-10 minutes per call on a topic of their choice. All conversations were collected outside North America.
Speech data is encoded as a-law, sampled at 8 kHz, and stored in SPHERE formatted files.
In addition to development and evaluation data, this corpus also contains trial lists, their associated keys, tables containing metadata information, and evaluation documentation.
Samples
For an example of the data in this corpus, please listen to this sample (SPH).
Updates
None at this time.