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A Speech Corpus for Modeling Language Acquisition: CAREGIVER
Aalto Univ. School of Science and Tech., Dept. of Signal Proc. & Acoustics.
Radboud University Nijmegen, Language and Speech unit.
Univ. of Sheffield, Speech & Hearing group, Dept. of Computer Science.
KTH, School of Electrical Engineering (EES), Sound and Image Processing.
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2010 (English)In: 7th International Conference on Language Resources and Evaluation (LREC) 2010, Valletta, Malta / [ed] Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias, European Language Resources Association (ELRA) , 2010, 1062-1068 p.Conference paper (Refereed)
Abstract [en]

A multi-lingual speech corpus used for modeling language acquisition called CAREGIVER has been designed and recorded within the framework of the EU funded Acquisition of Communication and Recognition Skills (ACORNS) project. The paper describes the motivation behind the corpus and its design by relying on current knowledge regarding infant language acquisition. Instead of recording infants and children, the voices of their primary and secondary caregivers were captured in both infant-directed and adult-directed speech modes over four languages in a read speech manner. The challenges and methods applied to obtain similar prompts in terms of complexity and semantics across different languages, as well as the normalized recording procedures employed at different locations, is covered. The corpus contains nearly 66000 utterance based audio files spoken over a two-year period by 17 male and 17 female native speakers of Dutch, English, Finnish, and Swedish. An orthographical transcription is available for every utterance. Also, time-aligned word and phone annotations for many of the sub-corpora also exist. The CAREGIVER corpus will be published via ELRA.

Place, publisher, year, edition, pages
European Language Resources Association (ELRA) , 2010. 1062-1068 p.
National Category
Language Technology (Computational Linguistics) Other Computer and Information Science
URN: urn:nbn:se:kth:diva-39052ISBN: 2-9517408-6-7OAI: diva2:439329
LREC 2010
QC 20111017Available from: 2011-09-07 Created: 2011-09-07 Last updated: 2011-10-17Bibliographically approved

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Koniaris, Christos
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Sound and Image Processing
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