Speaker adaptation using codebook integrated deep neural networks for speech enhancement
Year: 2024
Type: article
Abstract: Deep neural network (DNN) based speech enhancement techniques have shown superior performance compared to the traditional speech enhancement approaches in handling nonstationary noise. However, their performance is often compromised as a result of mismatch between their testing and training conditions. In this work, a codebook integrated deep neural network (CI-DNN) approach is introduced for speech enhancement, which mitigates this mismatch by employing existing speaker adapted codebooks with a DNN. The proposed CI-DNN demonstrates better speech enhancement performance compared to the corresponding speaker independent DNNs. The CI-DNN approach essentially involves a post processing operation for DNN and, hence, is applicable to any DNN architecture.
Source: JASA Express Letters
DOI: 10.1121/10.0034308
Authors: B Chidambar, D. Hanumanth Rao Naidu
Institution: Sri Sathya Sai University for Human Excellence
Language: English
Topic: Speech and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4404069963