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1
The Usefulness of Imperfect Speech Data for ASR Development in Low-Resource Languages
In: Information ; Volume 10 ; Issue 9 (2019)
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2
Afrikaans and Dutch as closely-related languages: A comparison to West Germanic languages and Dutch dialects
In: Stellenbosch Papers in Linguistics Plus, Vol 47, Iss 0, Pp 1-18 (2015) (2015)
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3
Speech data collection in an under-resourced language within a multilingual context,” in SLTU.
In: http://mica.edu.vn/sltu2014/proceedings/35.pdf (2014)
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4
Comparing classifiers for pronunciation error detection
In: http://academic.sun.ac.za/su_clast/documents/interspeech_2007_strik.pdf (2007)
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5
Nguni and Sotho varieties of South African English- distant cousins or twins?
In: http://isca-speech.org/archive_open/archive_papers/ml06/ml06_009.pdf (2006)
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6
Evaluation Of Formant-Like Features Forasr
In: http://lands.let.kun.nl/literature/dewet.2002.1.ps (2002)
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7
Using likelihood ratios to perform utterance verification in automatic pronunciation assessment
In: http://lands.let.ru.nl/TSpublic/strik/publications/a63.pdf (1999)
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8
Using Likelihood Ratios To Perform Utterance Verification In Automatic Pronunciation Assessment
In: http://lands.let.kun.nl/literature/dewet.1999.1.ps (1999)
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9
Automatic detection of frequent pronunciation errors made by L2-learners
In: http://lands.let.kun.nl/literature/truong.2005.1.pdf
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10
The Speect text-to-speech system entry for the Blizzard Challenge 2013
In: http://www.festvox.org/blizzard/bc2013/MERAKA_Blizzard2013.pdf
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11
Automatic large-scale oral language proficiency assessment
In: http://academic.sun.ac.za/su_clast/documents/interspeech_2007_dewet.pdf
Abstract: We describe first results obtained during the development of an automatic system for the assessment of spoken English profi-ciency of university students. The ultimate aim of this system is to allow fast, consistent and objective assessment of oral pro-ficiency for the purpose of placing students in courses appro-priate to their language skills. Rate of speech (ROS) was cho-sen as an indicator of fluency for a number of oral language exercises. In a test involving 106 student subjects, the assess-ments of 5 human raters are compared with evaluations based on automatically-derived ROS scores. It is found that, although the ROS is estimated accurately, the correlation between hu-man assessments and the ROS scores varies between 0.5 and 0.6. However, the results also indicate that only two of the five human raters were consistent in their appraisals, and that there was only mild inter-rater agreement. Index Terms: automatic oral proficiency assessment, rate of speech (ROS), computer assisted language learning (CALL). 1.
URL: http://academic.sun.ac.za/su_clast/documents/interspeech_2007_dewet.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.510.9617
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12
Wet, “The origin of Afrikaans pronunciation: a comparison to west Germanic languages and Dutch dialects
In: http://www.prasa.org/proceedings/2008/prasa08-22.pdf
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13
The origin of Afrikaans pronunciation: a comparison to west Germanic languages and Dutch dialects
In: http://www.let.rug.nl/%7Eheeringa/dialectology/papers/prasa08.pdf
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