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1
Multilingual Number Transcription for Text-to-Speech Conversion
In: http://www.cstr.ed.ac.uk/downloads/publications/2013/ssw8_PS1-8_San-Segundo.pdf (2013)
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2
DiarTk: An open source toolkit for research in multistream speaker diarization and its application to meetings recordings
In: http://publications.idiap.ch/downloads/papers/2012/Vijayasenan_INTERSPEECH2012_2012.pdf (2012)
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3
Recovering Capitalization and Punctuation Marks on Speech Transcriptions
In: http://www.propor2012.org/theses/FBatista_PROPOR2012-PhD.pdf (2011)
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4
Clin Linguist Phon Downloaded from informahealthcare.com by University of Minnesota For personal use only.
In: http://www.tc.umn.edu/%7Emunso005/MunsonEtAl2010.pdf (2009)
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5
partial automation
In: http://isca-speech.org/archive_open/archive_papers/exling2008/exl8_197.pdf (2008)
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6
Methodological questions in studying consonant acquisition
In: http://www.ling.ohio-state.edu/%7Eedwards/EdwardsBeckman2008proofsCLP.pdf (2008)
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7
Making use of bilingual interview data: Some expressions from the field
In: http://www.nova.edu/ssss/QR/QR12-3/halai.pdf (2007)
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8
Integrated Linguistic Resources for Language Exploitation Technologies
In: http://papers.ldc.upenn.edu/LREC2006/LREC_2006_GALE_Paper.pdf (2006)
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9
Integrated linguistic resources for language exploitation technologies
In: http://www.cs.brandeis.edu/~marc/misc/proceedings/lrec-2006/pdf/745_pdf.pdf (2006)
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10
Transitioning from analog to digital audio recording in childhood speech sound disorders
In: http://www.waisman.wisc.edu/phonology/pubs/PUB4.pdf (2005)
Abstract: Few empirical findings or technical guidelines are available on the current transition from analog to digital audio recording in childhood speech sound disorders. Of particular concern in the present context was whether a transition from analog- to digital-based transcription and coding of prosody and voice features might require re-standardizing a reference database for research in childhood speech sound disorders. Two research transcribers with different levels of experience glossed, transcribed, and prosody-voice coded conversational speech samples from eight children with mild to severe speech disorders of unknown origin. The samples were recorded, stored, and played back using representative analog and digital audio systems. Effect sizes calculated for an array of analog versus digital comparisons ranged from negligible to medium, with a trend for participants ’ speech competency scores to be slightly lower for samples obtained and transcribed using the digital system. We discuss the implications of these and other findings for research and clinical practise.
Keyword: Articulation; assessment; phonology; prosody; transcription
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.385.7700
http://www.waisman.wisc.edu/phonology/pubs/PUB4.pdf
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11
Marijn van Dijk a,∗, Paul van Geert b
In: http://www.paulvangeert.nl/publications_files/Disentagling pdf.pdf (2004)
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12
Abstract The Buckeye corpus of conversational speech: labeling conventions and a test of transcriber reliability
In: http://linguistics.berkeley.edu/~kjohnson/papers/Pitt_et_al.pdf (2004)
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13
The Arabic noun phrase. A minimalist approach
In: http://www.lotpublications.nl/publish/articles/000410/bookpart.pdf (2003)
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14
The LIMSI Broadcast News Transcription System
In: ftp://tlp.limsi.fr/public/spcH4_limsi.ps.Z (2002)
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15
Competing Creole Transcripts on Trial
In: http://privatewww.essex.ac.uk/~patrickp/papers/CreoleTranscripts.pdf (2000)
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16
Fast Speaker Change Detection for Broadcast News Transcription and Indexing
In: http://www.ee.columbia.edu/~dpwe/papers/LiuK99-spkrseg.pdf (1999)
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17
Title Specification of orthographic transcription and lexicon conventions Status Final Deliverable SD1.3.2 Work Package WP 1 Task Task 1.3
In: http://www.speechdat.org/speechdat/deliverables/public/sd132v24.pdf (1997)
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18
Quantitative Classification of Conversational Language Using Artificial Neural Networks
In: http://www.dcs.ex.ac.uk/research/pann/pdf/pann_SS_040.pdf (1997)
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19
Neural Networks In Spontaneous Speech Assessment Of Dysphasic Patients
In: http://www.dcs.ex.ac.uk/research/pann/pdf/pann_SS_041.pdf (1996)
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20
INTERSPEECH 2010 Predicting human perception and ASR classification of word-final [t] by its acoustic sub-segmental properties
In: http://lands.let.kun.nl/literature/schuppler.2010.2.pdf
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