Abstract
Optimal linear filtering has been used extensively for speech enhancement. In this paper, we take a first step in trying to apply linear filtering to the decomposition of a noisy speech signal into its components. The problem of decomposing speech into its voiced and unvoiced components is considered as an estimation problem. Assuming a harmonic model for the voiced speech, we propose a Wiener filtering scheme which estimates both components separately in the presence of noise. It is shown under which conditions this optimal filtering formulation outperforms two state-of-the-art speech decomposition methods, which is also revealed by objective measures, spectrograms and informal listening tests.
Original language | English |
---|---|
Title of host publication | 2018 26th European Signal Processing Conference (EUSIPCO) |
Number of pages | 5 |
Publisher | IEEE |
Publication date | 2018 |
Pages | 2325-2329 |
ISBN (Print) | 978-90-827970-0-8, 978-1-5386-3736-4 |
ISBN (Electronic) | 978-9-0827-9701-5 |
DOIs | |
Publication status | Published - 2018 |
Event | 26th European Signal Processing Conference - Rome, Italy Duration: 3 Sept 2018 → 7 Sept 2018 Conference number: 26 http://www.eusipco2018.org |
Conference
Conference | 26th European Signal Processing Conference |
---|---|
Number | 26 |
Country/Territory | Italy |
City | Rome |
Period | 03/09/2018 → 07/09/2018 |
Internet address |
Series | Proc. European Signal Processing Conference |
---|---|
ISSN | 2076-1465 |
Keywords
- speech decomposition
- time-domain filtering
- Wiener filter
- voiced speech
- unvoiced speech