Title:
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Creating an a cappella singing audio dataset for automatic Jingju singing evaluation research
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Author:
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Gong, Rong; Caro Repetto, Rafael; Serra, Xavier
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Abstract:
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Comunicació presentada al 4th International Workshop on Digital Libraries for Musicology celebrat el 28 d'octubre de 2017 a Shanghai, Xina. |
Abstract:
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e data-driven computational research on automatic jingju (also
known as Beijing or Peking opera) singing evaluation lacks a suitable
and comprehensive a cappella singing audio dataset. In this
work, we present an a cappella singing audio dataset which consists
of 120 arias, accounting for 1265 melodic lines. is dataset is also
an extension our existing CompMusic jingju corpus. Both professional
and amateur singers were invited to the dataset recording
sessions, and the most common jingju musical elements have been
covered. is dataset is also accompanied by metadata per aria and
melodic line annotated for automatic singing evaluation research
purpose. All the gathered data is openly available online. |
Abstract:
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This research was funded by the European Research Council under
the European Union's Seventh Framework Program, as part of
the CompMusic project (ERC grant agreement 267583). |
Subject(s):
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-A cappella singing -Automatic jingju singing evaluation -Audio recording dataset |
Rights:
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© 2017 Association for Computing Machinery
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Document type:
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Conference Object Article - Accepted version |
Published by:
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ACM Association for Computer Machinery
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