2008 NIST Speaker Recognition Evaluation Supplemental Set

Item Name: 2008 NIST Speaker Recognition Evaluation Supplemental Set
Author(s): NIST Multimodal Information Group
LDC Catalog No.: LDC2011S11
ISBN: 1-58563-601-0
ISLRN: 332-216-006-330-8
DOI: https://doi.org/10.35111/c0bt-hn95
Release Date: December 15, 2011
Member Year(s): 2011
DCMI Type(s): Sound
Sample Type: ulaw
Sample Rate: 8000
Data Source(s): microphone speech
Project(s): NIST SRE
Application(s): speaker identification
Language(s): English
Language ID(s): eng
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2011S11 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: NIST Multimodal Information Group. 2008 NIST Speaker Recognition Evaluation Supplemental Set LDC2011S11. Web Download. Philadelphia: Linguistic Data Consortium, 2011.
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2008 NIST Speaker Recognition Evaluation Supplemental Set, Linguistic Data Consortium (LDC) catalog number LDC2011S11 and ISBN 1-58563-601-0, was developed by LDC and NIST (National Institute of Standards and Technology) and contains additional data distributed after the main 2008 Speaker Recognition Evaluation (SRE). Specifically, the corpus consists of 770 hours of English microphone speech along with transcripts and other materials used as supplemental data in the 2008 NIST Speaker Recognition Evaluation (SRE) and in a follow-up evaluation to SRE08.

NIST SRE is part of an ongoing series of evaluations conducted by NIST. These evaluations are an important contribution to the direction of research efforts and the calibration of technical capabilities. They are intended to be of interest to all researchers working on the general problem of text independent speaker recognition. To this end the evaluation is designed to be simple, to focus on core technology issues, to be fully supported, and to be accessible to those wishing to participate.

The 2008 evaluation was distinguished from prior evaluations, in particular those in 2005 and 2006, by including not only conversational telephone speech data but also conversational speech data of comparable duration recorded over a microphone channel involving an interview scenario.The follow-up evaluation focused on speaker detection in the context of conversational interview type speech and was designed to measure the performance of SRE08 systems in previously unexposed test segment channel conditions.

LDC previously released the main 2008 NIST SRE Evaluation in three parts as 2008 NIST Speaker Recognition Evaluation Training Set Part 1 LDC2011S05, 2008 NIST Speaker Recognition Evaluation Training Set Part 2 LDC2011S07 and 2008 NIST Speaker Recognition Evaluation Test Set LDC2011S08.

Additional documentation is available in the 2008 SRE Evaluation Plan and the Plan for Follow-up Evaluation to SRE08.


The speech data in this release was collected in 2007 by LDC at its Human Subjects Data Collection Laboratories in Philadelphia and by the International Computer Science Institute (ICSI) at the University of California, Berkeley. This collection was part of the Mixer 5 project, which was designed to support the development of robust speaker recognition technology by providing carefully collected and audited speech from a large pool of speakers recorded simultaneously across numerous microphones and in different communicative situations and/or in multiple languages. Mixer participants were native English and bilingual English speakers. The microphone speech in this corpus is in English and consists of approximately 3 minute and 30 minute interview excerpts..

This supplemental data is split into four different parts which provide:

  • new training data distributed to 2008 SRE participants
  • additional data distributed to participants in the 2008 SRE follow-up evaluation
  • interviewer channel files for the 2008 SRE main test (released after the evaluations)
  • supplemental training data (released after the evaluations)

English language transcripts in .cfm format were produced using an automatic speech recognition (ASR) system and are included for some, but not all, speech data.


For an example of the data contained in this corpus, review this audio sample.


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