@inproceedings{andrassy-hoege-2006-human,
title = "Human and machine recognition as a function of {SNR}",
author = "Andrassy, Bernt and
Hoege, Harald",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Gangemi, Aldo and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Tapias, Daniel",
booktitle = "Proceedings of the Fifth International Conference on Language Resources and Evaluation ({LREC}{'}06)",
month = may,
year = "2006",
address = "Genoa, Italy",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2006/pdf/179_pdf.pdf",
abstract = "In-car automatic speech recognition (ASR) is usually evaluated behaviour for different levels of noise. Yet this is interesting for car manufacturers in order to predict system performances for different speeds and different car models and thus allow to design speech based applications in a better way. It therefore makes sense to split the single WER into SNR dependent WERs, where SNR stands for the signal to noise ratio, which is an appropriate measure for the noise level. In this paper a SNR measure based on the concept of the Articulation Index is developed, which allows the direct comparison with human recognition performance.",
}
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<abstract>In-car automatic speech recognition (ASR) is usually evaluated behaviour for different levels of noise. Yet this is interesting for car manufacturers in order to predict system performances for different speeds and different car models and thus allow to design speech based applications in a better way. It therefore makes sense to split the single WER into SNR dependent WERs, where SNR stands for the signal to noise ratio, which is an appropriate measure for the noise level. In this paper a SNR measure based on the concept of the Articulation Index is developed, which allows the direct comparison with human recognition performance.</abstract>
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%0 Conference Proceedings
%T Human and machine recognition as a function of SNR
%A Andrassy, Bernt
%A Hoege, Harald
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Gangemi, Aldo
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Tapias, Daniel
%S Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
%D 2006
%8 May
%I European Language Resources Association (ELRA)
%C Genoa, Italy
%F andrassy-hoege-2006-human
%X In-car automatic speech recognition (ASR) is usually evaluated behaviour for different levels of noise. Yet this is interesting for car manufacturers in order to predict system performances for different speeds and different car models and thus allow to design speech based applications in a better way. It therefore makes sense to split the single WER into SNR dependent WERs, where SNR stands for the signal to noise ratio, which is an appropriate measure for the noise level. In this paper a SNR measure based on the concept of the Articulation Index is developed, which allows the direct comparison with human recognition performance.
%U http://www.lrec-conf.org/proceedings/lrec2006/pdf/179_pdf.pdf
Markdown (Informal)
[Human and machine recognition as a function of SNR](http://www.lrec-conf.org/proceedings/lrec2006/pdf/179_pdf.pdf) (Andrassy & Hoege, LREC 2006)
ACL
- Bernt Andrassy and Harald Hoege. 2006. Human and machine recognition as a function of SNR. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).