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Comparing classifiers for pronunciation error detection
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In: http://academic.sun.ac.za/su_clast/documents/interspeech_2007_strik.pdf (2007)
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JASMIN-CGN: Extension of the Spoken Dutch Corpus with speech of elderly people, children and nonnatives in the human-machine interaction modality
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In: http://taalunieversum.org/archief/taal/technologie/stevin/documenten/LREC2006-jasminpap07.pdf (2006)
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Jasmin-cgn: Extension of the spoken dutch corpus with speech of elderly people, children and non-natives in the human-machine interaction modality
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In: http://www.cs.brandeis.edu/~marc/misc/proceedings/lrec-2006/pdf/254_pdf.pdf (2006)
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Selecting segmental errors in non-native Dutch for optimal pronunciation training
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In: http://lands.let.kun.nl/literature/neri.2006.3.pdf (2006)
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| 5 |
Multiword Expressions in Spoken Language: An Exploratory Study on Pronunciation Variation
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In: http://lands.let.kun.nl/literature/binnenpoorte.2005.1.pdf (2005)
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Automatic pronunciation error detection: an acoustic-phonetic approach
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In: http://isca-speech.org/archive_open/archive_papers/icall2004/iic4_032.pdf (2004)
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Improving automatic phonetic transcription of spontaneous speech through variant-based pronunciation variation modelling
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In: http://www.lrec-conf.org/proceedings/lrec2004/pdf/558.pdf (2004)
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| 8 |
Improving Automatic Phonetic Transcription of Spontaneous Speech through Variant-Based Pronunciation Variation Modelling
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In: http://lands.let.kun.nl/literature/binnenpoorte.2004.1.pdf (2004)
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| 9 |
Automatic Phonetic Transcription: An Overview
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In: http://lands.let.kun.nl/literature/catia.2003.1.pdf (2003)
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How to Improve Human and Machine Transcriptions of Spontaneous Speech
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In: http://lands.let.kun.nl/literature/binnenpoorte.2003.2.pdf (2003)
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| 11 |
How to Improve Human and Machine Transcriptions of Spontaneous Speech
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In: http://lands.let.ru.nl/cgn/publs/ssprcgn.pdf (2003)
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| 12 |
Phonetic Transcription of Large Speech Corpora: How to boost efficiency without affecting quality
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In: http://lands.let.kun.nl/literature/binnenpoorte.2003.1.pdf (2003)
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| 13 |
Validation and Improvement of Automatic Phonetic Transcriptions
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In: http://lands.let.kun.nl/literature/catia.2002.1.pdf (2002)
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| 14 |
/r/-deletion in Dutch: rumours or reality?
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In: http://lands.let.kun.nl/literature/heuvel.2001.6.ps (2001)
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| 15 |
Obtaining Phonetic Transcriptions: A Comparison between Expert Listeners and a Continuous Speech Recognizer
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In: http://lands.let.kun.nl/literature/wester.2001.3.pdf (2001)
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| 16 |
Effective feedback on L2 pronunciation in ASR-based CALL
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In: http://lands.let.ru.nl/TSpublic/strik/publications/a77.pdf (2001)
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Abstract:
Computer Assisted Language Learning (CALL) has now established itself as a prolific area whose advantages are well-known to educators. Yet, many authors lament the lack of a reliable integrated conceptual framework linking technology advances and second language acquisition research within which effective materials can be designed [1],[2]. The CALL world has recently witnessed a flourishing of software applications among which Automatic Speech Recognition (ASR) is gaining growing importance. The reasons for this popularity lie in the opportunities this technology offers for practising oral skills and addressing pronunciation problems, two areas that are hard to improve within traditional class-based settings. ASR-based CALL systems appear to be particularly suited for pronunciation teaching as they allow evaluation of the learner’s speech and provide appropriate, individual feedback in real-time. However, given the lack of guidelines for CALL design, most courseware products often do not provide adequate guidance to the learner [3],[4]. Moreover, owing to the limitations in the state-of-the-art technology, all ASR systems will at times generate errors [4]. The main objective of our research is to study how the frequency and seriousness of feedback errors
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.192.210
http://lands.let.ru.nl/TSpublic/strik/publications/a77.pdf
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| 17 |
Effective feedback on L2 pronunciation in ASR-based CALL
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In: http://lands.let.kun.nl/literature/neri.2001.1.pdf (2001)
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| 18 |
Effective feedback on L2 pronunciation in ASR-based CALL
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In: http://lands.let.kun.nl/literature/neri.2001.1.ps (2001)
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| 19 |
Quantitative assessment of second language learners' fluency by means of automatic speech recognition technology
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In: http://www.cs.columbia.edu/~amaxwell/candidacy/l2learning/catia.1998.3.pdf (2000)
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| 20 |
Postvocalic /r/-Deletion In Dutch: More Experimental Evidence
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In: http://iris1.let.kun.nl/literature/heuvel.1999.3.ps (1999)
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