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The EASR Corpora of European Portuguese, French, Hungarian and Polish Elderly Speech

Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014)

DOI:10.63317/4q8pyto7qurj

Abstract

Currently available speech recognisers do not usually work well with elderly speech. This is because several characteristics of speech (e.g. fundamental frequency, jitter, shimmer and harmonic noise ratio) change with age and because the acoustic models used by speech recognisers are typically trained with speech collected from younger adults only. To develop speech-driven applications capable of successfully recognising elderly speech, this type of speech data is needed for training acoustic models from scratch or for adapting acoustic models trained with younger adults’ speech. However, the availability of suitable elderly speech corpora is still very limited. This paper describes an ongoing project to design, collect, transcribe and annotate large elderly speech corpora for four European languages: Portuguese, French, Hungarian and Polish. The Portuguese, French and Polish corpora contain read speech only, whereas the Hungarian corpus also contains spontaneous command and control type of speech. Depending on the language in question, the corpora contain 76 to 205 hours of speech collected from 328 to 986 speakers aged 60 and over. The final corpora will come with manually verified orthographic transcriptions, as well as annotations for filled pauses, noises and damaged words.

Details

Paper ID
lrec2014-main-316
Pages
pp. 1458-1464
BibKey
hamalainen-etal-2014-easr
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
978-2-9517408-8-4
Conference
Ninth International Conference on Language Resources and Evaluation
Location
Reykjavik, Iceland
Date
26 May 2014 31 May 2014

Authors

  • AH

    Annika Hämäläinen

  • JA

    Jairo Avelar

  • SR

    Silvia Rodrigues

  • MD

    Miguel Sales Dias

  • AK

    Artur Kolesiński

  • TF

    Tibor Fegyó

  • GN

    Géza Németh

  • PC

    Petra Csobánka

  • KL

    Karine Lan

  • DH

    David Hewson

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