On Optimal Filtering for Speech Decomposition

Alfredo Esquivel Jaramillo, Jesper Kjær Nielsen, Mads Græsbøll Christensen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

4 Citations (Scopus)
182 Downloads (Pure)

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 languageEnglish
Title of host publication2018 26th European Signal Processing Conference (EUSIPCO)
Number of pages5
PublisherIEEE
Publication date2018
Pages2325-2329
ISBN (Print)978-90-827970-0-8, 978-1-5386-3736-4
ISBN (Electronic)978-9-0827-9701-5
DOIs
Publication statusPublished - 2018
Event26th European Signal Processing Conference - Rome, Italy
Duration: 3 Sept 20187 Sept 2018
Conference number: 26
http://www.eusipco2018.org

Conference

Conference26th European Signal Processing Conference
Number26
Country/TerritoryItaly
CityRome
Period03/09/201807/09/2018
Internet address
SeriesProc. European Signal Processing Conference
ISSN2076-1465

Keywords

  • speech decomposition
  • time-domain filtering
  • Wiener filter
  • voiced speech
  • unvoiced speech

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