Track and Noise Separation Based on the Universal Codebook and Enhanced Speech Recognition Using Hybrid Deep Learning Method

Track and Noise Separation Based on the Universal Codebook and Enhanced Speech Recognition Using Hybrid Deep Learning Method

The concept of Deep learning is a part of machine learning which is very useful nowadays to achieve accurate voice and speech recognition based on the training data by creating robust algorithms. It is also possible to separate the noise from original speech as well as the separation of tracks in pa...

Full description

Bibliographic Details
Main Authors: S. V. Aswin Kumer, Lakshmi Bharath Gogu, E. Mohan, Suman Maloji, Balaji Natarajan, G. Sambasivam, Vaibhav Bhushan Tyagi
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Blind source separation (BSS) method
deep learning method
generative adversarial networks (GAN)
multi-channel method
noise separation
speech recognition
Online Access:https://ieeexplore.ieee.org/document/10298228/

Internet

https://ieeexplore.ieee.org/document/10298228/

Similar Items