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Dias, Miguel Sales (2014). Automatically recognising European Portuguese children’s speech: Pronunciation patterns revealed by an analysis of ASR errors. In Baptista, J., Mamede, N., Candeias, S., Paraboni, I., Pardo, T.A.S., Volpe Nunes, M.d.G. (Ed.), Computational Processing of the Portuguese Language. (pp. 1-11). Switzerland: Springer International Publishing.
J. M. Dias, "Automatically recognising European Portuguese children’s speech: Pronunciation patterns revealed by an analysis of ASR errors", in Computational Processing of the Portuguese Language, Baptista, J., Mamede, N., Candeias, S., Paraboni, I., Pardo, T.A.S., Volpe Nunes, M.d.G. , Ed., Switzerland, Springer International Publishing, 2014, vol. 8775, pp. 1-11
@incollection{dias2014_1734979112008, author = "Dias, Miguel Sales", title = "Automatically recognising European Portuguese children’s speech: Pronunciation patterns revealed by an analysis of ASR errors", booktitle = "Computational Processing of the Portuguese Language", year = "2014", volume = "8775", series = "Lecture Notes in Artificial Intelligence", edition = "Lecture Notes in Computer Science ", pages = "1-1", publisher = "Springer International Publishing", address = "Switzerland", url = "http://www.scopus.com/inward/record.url?eid=2-s2.0-84908567142&partnerID=MN8TOARS" }
TY - CHAP TI - Automatically recognising European Portuguese children’s speech: Pronunciation patterns revealed by an analysis of ASR errors T2 - Computational Processing of the Portuguese Language VL - 8775 AU - Dias, Miguel Sales PY - 2014 SP - 1-11 DO - 10.1007/978-3-319-09761-9 CY - Switzerland UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-84908567142&partnerID=MN8TOARS AB - This paper reports findings from an analysis of errors made by an automatic speech recogniser trained and tested with 3-10-year-old European Portuguese children’s speech. We expected and were able to identify frequent pronunciation error patterns in the children’s speech. Furthermore, we were able to correlate some of these pronunciation error patterns and automatic speech recognition errors. The findings reported in this paper are of phonetic interest but will also be useful for improving the performance of automatic speech recognisers aimed at children representing the target population of the study. ER -