2016 NIST speaker recognition evaluation : test set / Linguistic Data Consortium.

1585639044

[Philadelphia, PA] : [Linguistic Data Consortium], [2019]

1 online resource

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"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. 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 ten 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 8kHz, 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." --LDC online catalog.

Audio / Data Sets / Online

Multiple languages; Tagalog; Chinese; Cebuano

September 28, 2020