Corpus ID: 195749513

A Model-Driven Exploration of Accent Within the Amateur Singing Voice

@inproceedings{Noufi2019AME,
  title={A Model-Driven Exploration of Accent Within the Amateur Singing Voice},
  author={Camille Noufi and Vidya Rangasayee and Sarah Ciresi and J. Berger and Blair Kaneshiro},
  year={2019}
}
  • Camille Noufi, Vidya Rangasayee, +2 authors Blair Kaneshiro
  • Published 2019
  • We seek to detect characteristics of regional language accent in solo singing using two variants of convolutional neural networks to classify reported country and language from ten countries during karaoke-style vocal performance of the broadly popular hymn, Amazing Grace. The most successful model produces overall accuracy of 15.64%, with false classification of singing segments to be variants of English at 53.4%. The model also separates learned classes along a rhythmic-stress dimension with… CONTINUE READING
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