Speech in Noisy Environments (SPINE) Evaluation Transcripts

Item Name: Speech in Noisy Environments (SPINE) Evaluation Transcripts
Author(s): Astrid Schmidt-Nielsen, Elaine Marsh, Christopher Cieri, Stephanie Strassel, Kara Rennert
LDC Catalog No.: LDC2000T54
ISBN: 1-58563-189-2
ISLRN: 742-218-645-985-8
Release Date: June 17, 2002
Member Year(s): 2000
DCMI Type(s): Text
Data Source(s): microphone speech, microphone conversation
Project(s): SPINE
Application(s): speech recognition
Language(s): English
Language ID(s): eng
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2000T54 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Schmidt-Nielsen, Astrid, et al. Speech in Noisy Environments (SPINE) Evaluation Transcripts LDC2000T54. Web Download. Philadelphia: Linguistic Data Consortium, 2000.

Introduction

This publication contains the Speech in Noisy Environments (SPINE) Evaluation Transcripts, created for the Department of Defense (DoD) Digital Voice Processing Consortium (DDVPC) by Arcon Corp., and produced by the Linguistic Data Consortium (LDC) catalog number LDC2000T54 and ISBN 1-58563-189-2. A companion corpus, Speech in Noisy Environments (SPINE) Evaluation Audio, was also produced by the Linguistic Data Consortium (LDC); catalog number LDC2000S96, ISBN 1-58563-188-4. These corpora support the 2000 Speech in Noisy Environments evaluation. For an example transcript, please click here.

The 2000 Speech in Noisy Environments Evaluation (SPINE1) is a first attempt to assess the state of the art and practice in speech recognition technology in noisy military environments and to exchange information on innovative speech recognition technology in the context of fully implemented systems that perform realistic tasks. It is intended to be of interest to all university, industrial and commercial speech system developers working on the problem of robust speech recognition. The evaluation gives participants the opportunity to participate in a flexible evaluation, suited to development needs and abilities.

This work was sponsored in part by National Science Foundation Grant No. IIS-9982201.

Data

The SPINE1 evaluation focuses on the task of transcribing speech produced in noisy environments with the emphasis on speech produced in noisy military environments. The evaluation is designed to promote research progress in this area, to provide the opportunity for participants to try out new ideas for developing robust speech recognition systems that are of both scientific and practical interest, and to measure the performance of this technology. More information on this evaluation is available at SPINE1.

The evaluation task is to transcribe speech produced in noisy environments. The training and test speech data to be used for this evaluation were generated by ARCON Corp. for the DoD Digital Voice Processing Consortium (DDVPC) under controlled conditions. The speech data consists of conversations between two communicators working on a collaborative, Battleship-like task in which they seek and shoot at targets (ARCON Communicability Exercise, ACE). Participants may talk freely, but the total vocabulary used is fairly limited. Each person is seated in a sound chamber in which a previously recorded military background noise environment is accurately reproduced. The participants use handsets and transmission channels that are resident to the particular environment. The evaluation data includes 20 talker-pairs, with six five-minutes conversations per talker-pair (about 600 minutes total), from a set of four scenarios

Updates

August 13, 2001: A tagging error was discovered in which several files containing occurrences of the incorrect tag "[{noise}]," were converted to the correct tag, "[/noise]." There were 433 occurrences of this error across all files. Also, a single occurrence of two instances of "[noise/]" on the same line was corrected to "[/noise]" in the second instance. If you previously purchased this corpus and would like to download a corrected copy please contact ldc@ldc.upenn.edu.

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