A convolutional recurrent neural network with attention framework for speech separation in monaural recordings

Most speech separation studies in monaural channel use only a single type of network, and the separation effect is typically not satisfactory, posing difficulties for high quality speech separation. In this study, we propose a convolutional recurrent neural network with an attention (CRNN-A) framewo...

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Detalles Bibliográficos
Autores principales: Sun, Chao, Zhang, Min, Wu, Ruijuan, Lu, Junhong, Xian, Guo, Yu, Qin, Gong, Xiaofeng, Luo, Ruisen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809293/
https://www.ncbi.nlm.nih.gov/pubmed/33446851
http://dx.doi.org/10.1038/s41598-020-80713-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809293/
https://www.ncbi.nlm.nih.gov/pubmed/33446851
http://dx.doi.org/10.1038/s41598-020-80713-3

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