2017 NIST Language Recognition Evaluation Training and Development Sets, Linguistic Data Consortium (LDC) catalog number LDC2022S10 and ISBN 1-58563-999-0, contains training and development material for the 2017 NIST Language Recognition Evaluation. It consists of approximately 2,100 hours of conversational telephone speech, broadcast conversation, broadcast narrow band speech, and speech from video in the following 14 languages, dialects, and varieties: Arabic (Iraqi, Levantine, Maghrebi, Egyptian), English (British, American), Polish, Russian, Portuguese (Brazilian), Spanish (Caribbean, European, Latin American Continental), and Chinese (Mandarin, Min Nan).
The goal of the NIST (National Institute of Standards and Technology) Language Recognition Evaluation (LRE) is to establish the baseline of current performance capability for language recognition of conversational telephone speech and to lay the groundwork for further research efforts in the field. NIST conducted language recognition evaluations in 1996, 2003, 2005, 2007, 2009, 2011, and 2015. The 2017 evaluation focused on differentiating closely related language pairs. In addition to conversational telephone speech, broadcast conversation, and broadcast narrow band speech, speech excerpts extracted from video data were used. Further information regarding this evaluation can be found in the evaluation plan which is also included in the documentation for this release.
LDC released the prior LREs as:
This release includes data from LDC's CALLFRIEND and Fisher telephone collections, the VAST video collection, various broadcast sources and earlier NIST LRE test sets.
The training audio files are single-channel, 8-KHz sample rate in NIST SPHERE format, either mu-law, A-law or 16-bit PCM. The development audio files are also single-channel, but vary in format: either SPHERE or FLAC-compressed MSWAV (RIFF). All "*.flac" files are 16-bit PCM, 44.1 KHz sample rate; the "*.sph" files are all 8-KHz, with either mu-law or 16-bit PCM samples.
Please see file.tbl for a complete file list as well as checksums for this publication.
Additional information, updates, bug fixes may be available in the LDC catalog entry for this corpus at LDC2022S10.
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