Parameter masks for close talk speech segregation using deep neural networks
A deep neural networks (DNN) based close talk speech segregation algorithm is introduced. One nearby microphone is used to collect the target speech as close talk indicated, and another microphone is used to get the noise in environments. The time and energy difference between the two microphones si...
Main Authors: | Jiang Yi, Liu Runsheng |
---|---|
Format: | Article |
Language: | English |
Published: |
EDP Sciences
2015-01-01
|
Series: | MATEC Web of Conferences |
Online Access: | http://dx.doi.org/10.1051/matecconf/20153117004 |
Similar Items
-
The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility.
by: Thomas Bentsen, et al.
Published: (2018-01-01) -
A hybrid technique for speech segregation and classification using a sophisticated deep neural network.
by: Khurram Ashfaq Qazi, et al.
Published: (2018-01-01) -
Multi-resolution auditory cepstral coefficient and adaptive mask for speech enhancement with deep neural network
by: Ruwei Li, et al.
Published: (2019-04-01) -
Using Energy Difference for Speech Separation of Dual-microphone Close-talk System
by: Yi Jiang, et al.
Published: (2013-05-01) -
Components loss for neural networks in mask-based speech enhancement
by: Ziyi Xu, et al.
Published: (2021-07-01)