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Unsupervised learning of phonemes of whispered speech in a noisy environment based on convolutive non-negative matrix factorization

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Publication:498019
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DOI10.1016/j.ins.2013.09.037zbMath1320.68157OpenAlexW2021954339MaRDI QIDQ498019

Yong-Cai Geng, Sumit K. Garg

Publication date: 25 September 2015

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2013.09.037


zbMATH Keywords

non-negative matrix factorizationunsupervised phoneme base learningwhisper intelligibility enhancement


Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10) Measures of information, entropy (94A17)


Related Items

Robust Manhattan non-negative matrix factorization for image recovery and representation ⋮ Lagrange stability of neural networks with memristive synapses and multiple delays ⋮ Projective robust nonnegative factorization



Cites Work

  • Multi-adjoint property-oriented and object-oriented concept lattices
  • Rough set model based on formal concept analysis
  • The auditory organization of speech and other sources in listeners and computational models
  • Learning the parts of objects by non-negative matrix factorization
  • Speech enhancement for non-stationary noise environments
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