Spatial position constraint for unsupervised learning of speech representations

The success of supervised learning techniques for automatic speech processing does not always extend to problems with limited annotated speech. Unsupervised representation learning aims at utilizing unlabelled data to learn a transformation that makes speech easily distinguishable for classification...

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Detalles Bibliográficos
Autores principales: Humayun, Mohammad Ali, Yassin, Hayati, Abas, Pg Emeroylariffion
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8323719/
https://www.ncbi.nlm.nih.gov/pubmed/34395866
http://dx.doi.org/10.7717/peerj-cs.650

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8323719/
https://www.ncbi.nlm.nih.gov/pubmed/34395866
http://dx.doi.org/10.7717/peerj-cs.650

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