@inproceedings{graff-etal-2014-rats,
title = "The {RATS} Collection: Supporting {HLT} Research with Degraded Audio Data",
author = "Graff, David and
Walker, Kevin and
Strassel, Stephanie and
Ma, Xiaoyi and
Jones, Karen and
Sawyer, Ann",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/1125_Paper.pdf",
pages = "1970--1977",
abstract = "The DARPA RATS program was established to foster development of language technology systems that can perform well on speaker-to-speaker communications over radio channels that evince a wide range in the type and extent of signal variability and acoustic degradation. Creating suitable corpora to address this need poses an equally wide range of challenges for the collection, annotation and quality assessment of relevant data. This paper describes the LDCs multi-year effort to build the RATS data collection, summarizes the content and properties of the resulting corpora, and discusses the novel problems and approaches involved in ensuring that the data would satisfy its intended use, to provide speech recordings and annotations for training and evaluating HLT systems that perform 4 specific tasks on difficult radio channels: Speech Activity Detection (SAD), Language Identification (LID), Speaker Identification (SID) and Keyword Spotting (KWS).",
}
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<abstract>The DARPA RATS program was established to foster development of language technology systems that can perform well on speaker-to-speaker communications over radio channels that evince a wide range in the type and extent of signal variability and acoustic degradation. Creating suitable corpora to address this need poses an equally wide range of challenges for the collection, annotation and quality assessment of relevant data. This paper describes the LDCs multi-year effort to build the RATS data collection, summarizes the content and properties of the resulting corpora, and discusses the novel problems and approaches involved in ensuring that the data would satisfy its intended use, to provide speech recordings and annotations for training and evaluating HLT systems that perform 4 specific tasks on difficult radio channels: Speech Activity Detection (SAD), Language Identification (LID), Speaker Identification (SID) and Keyword Spotting (KWS).</abstract>
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%0 Conference Proceedings
%T The RATS Collection: Supporting HLT Research with Degraded Audio Data
%A Graff, David
%A Walker, Kevin
%A Strassel, Stephanie
%A Ma, Xiaoyi
%A Jones, Karen
%A Sawyer, Ann
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F graff-etal-2014-rats
%X The DARPA RATS program was established to foster development of language technology systems that can perform well on speaker-to-speaker communications over radio channels that evince a wide range in the type and extent of signal variability and acoustic degradation. Creating suitable corpora to address this need poses an equally wide range of challenges for the collection, annotation and quality assessment of relevant data. This paper describes the LDCs multi-year effort to build the RATS data collection, summarizes the content and properties of the resulting corpora, and discusses the novel problems and approaches involved in ensuring that the data would satisfy its intended use, to provide speech recordings and annotations for training and evaluating HLT systems that perform 4 specific tasks on difficult radio channels: Speech Activity Detection (SAD), Language Identification (LID), Speaker Identification (SID) and Keyword Spotting (KWS).
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/1125_Paper.pdf
%P 1970-1977
Markdown (Informal)
[The RATS Collection: Supporting HLT Research with Degraded Audio Data](http://www.lrec-conf.org/proceedings/lrec2014/pdf/1125_Paper.pdf) (Graff et al., LREC 2014)
ACL
- David Graff, Kevin Walker, Stephanie Strassel, Xiaoyi Ma, Karen Jones, and Ann Sawyer. 2014. The RATS Collection: Supporting HLT Research with Degraded Audio Data. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 1970–1977, Reykjavik, Iceland. European Language Resources Association (ELRA).