Speech in Noisy Environments 1 (SPINE1 CODED) Coded Audio
Item Name: | Speech in Noisy Environments 1 (SPINE1 CODED) Coded Audio |
Author(s): | Astrid Schmidt-Nielsen, Elaine Marsh, John Tardelli, Paul Gatewood, Elizabeth Kreamer, Thomas Tremain, Christopher Cieri, David Graff, Cristina Tofan, Kai Shun Soo |
LDC Catalog No.: | LDC2001S99 |
ISBN: | 1-58563-200-7 |
ISLRN: | 688-490-070-931-9 |
DOI: | https://doi.org/10.35111/spr5-mm07 |
Member Year(s): | 2001 |
DCMI Type(s): | Sound |
Sample Rate: | 16000 |
Data Source(s): | microphone speech |
Project(s): | SPINE |
Application(s): | speech recognition |
Language(s): | English |
Language ID(s): | eng |
License(s): |
LDC User Agreement for Non-Members |
Online Documentation: | LDC2001S99 Documents |
Licensing Instructions: | Subscription & Standard Members, and Non-Members |
Citation: | Schmidt-Nielsen, Astrid, et al. Speech in Noisy Environments 1 (SPINE1 CODED) Coded Audio LDC2001S99. Web Download. Philadelphia: Linguistic Data Consortium, 2001. |
Related Works: | View |
Introduction
Speech in Noisy Environments 1 (SPINE1 CODED) Coded Audio contains the Speech in Noisy Environments 1 (SPINE1) Coded Audio Corpus created for the Department of Defense (DoD) Digital Voice Processing Consortium (DDVPC) by Arcon Corp. The transcripts for this publication are available as Speech in Noisy Environments (SPINE1) Training Transcripts LDC2000T49 and Speech in Noisy Environments (SPINE1) Evaluation Transcripts LDC2000T54.
This work was sponsored in part by National Science Foundation Grant No. IIS-9982201.
Data
For an example transcript, please click here. There are a total of 253 files, one "game" each, for a rough total of 19 hours and 28 minutes (~4.4Gb) of audio data.
This corpus was used as part of the training set for the Second Speech in Noisy Environments Evaluation (SPINE2). SPINE2 provided a continuing forum for assessing the state of the art and practice in speech recognition technology for noisy military environments and for exchanging information on innovative speech recognition technology in the context of fully implemented systems that perform realistic tasks. The evaluation provided researchers, potential sponsors, and customers with a quantitative means to appreciate the strengths and weaknesses of the technologies.
Updates
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