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Hämäläinen, A., Moreira, F. P., Avelar, J., Braga, D. & Dias, M. S. (2013). Transcribing and annotating speech corpora for speech recognition: A three-step crowdsourcing approach with quality control. In Hartmann, B., and Horvitz, E. (Ed.), Proceedings of the 1st AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2013. (pp. 30-31). Palm Springs, California, USA: AAAI Press.
Export Reference (IEEE)
A. Hämäläinen et al.,  "Transcribing and annotating speech corpora for speech recognition: A three-step crowdsourcing approach with quality control", in Proc. of the 1st AAAI Conf. on Human Computation and Crowdsourcing, HCOMP 2013, Hartmann, B., and Horvitz, E., Ed., Palm Springs, California, USA, AAAI Press, 2013, vol. WS-13-18, pp. 30-31
Export BibTeX
@inproceedings{hämäläinen2013_1716153266064,
	author = "Hämäläinen, A. and Moreira, F. P. and Avelar, J. and Braga, D. and Dias, M. S.",
	title = "Transcribing and annotating speech corpora for speech recognition: A three-step crowdsourcing approach with quality control",
	booktitle = "Proceedings of the 1st AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2013",
	year = "2013",
	editor = "Hartmann, B., and Horvitz, E.",
	volume = "WS-13-18",
	number = "",
	series = "",
	doi = "10.1609/hcomp.v1i1.13102",
	pages = "30-31",
	publisher = "AAAI Press",
	address = "Palm Springs, California, USA",
	organization = "Association for the Advancement of Artificial Intelligence",
	url = "https://ojs.aaai.org/index.php/HCOMP/issue/view/315"
}
Export RIS
TY  - CPAPER
TI  - Transcribing and annotating speech corpora for speech recognition: A three-step crowdsourcing approach with quality control
T2  - Proceedings of the 1st AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2013
VL  - WS-13-18
AU  - Hämäläinen, A.
AU  - Moreira, F. P.
AU  - Avelar, J.
AU  - Braga, D.
AU  - Dias, M. S.
PY  - 2013
SP  - 30-31
DO  - 10.1609/hcomp.v1i1.13102
CY  - Palm Springs, California, USA
UR  - https://ojs.aaai.org/index.php/HCOMP/issue/view/315
AB  - Large speech corpora with word-level transcriptions annotated for noises and disfluent speech are necessary for training automatic speech recognisers. Crowdsourcing is a lower-cost, faster-turnaround, highly scalable alternative for expert transcription and annotation. In this paper, we showcase our three-step crowdsourcing approach motivated by the importance of accurate transcriptions and annotations.
ER  -