Spatio-temporal filtering methods for enhancement and separation of speech signals
(2013) 2013 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP) p.303-307- Abstract
- In this paper, we give an overview of the background for, the ideas behind, and the challenges to be addressed in the project "Spatio-Temporal Filtering Methods for Enhancement and Separation of Speech Signals," which is funded by the Villum Foundation. The project aims at addressing the problem of enhancing and separating speech signals from noisy mixtures, a problem also known as the cocktail party problem. It aims at exploring new ways of solving this problem by generalizing a new class of optimal temporal filtering methods for periodic signals to multiple microphones, resulting in so-called spatio-temporal filtering methods that are controlled by two parameters, the direction-of-arrival and the fundamental frequency. These filters are... (More)
- In this paper, we give an overview of the background for, the ideas behind, and the challenges to be addressed in the project "Spatio-Temporal Filtering Methods for Enhancement and Separation of Speech Signals," which is funded by the Villum Foundation. The project aims at addressing the problem of enhancing and separating speech signals from noisy mixtures, a problem also known as the cocktail party problem. It aims at exploring new ways of solving this problem by generalizing a new class of optimal temporal filtering methods for periodic signals to multiple microphones, resulting in so-called spatio-temporal filtering methods that are controlled by two parameters, the direction-of-arrival and the fundamental frequency. These filters are optimal in that they let the signal of interest pass undistorted while everything else is attenuated as much as possible. Unlike state-of-the-art methods, they do not require knowledge of the statistics of noise and interfering speech signals, something that is especially important when dealing with non-stationary noise. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3991188
- author
- Christensen, Mads ; Jensen, Jesper ; Benesty, Jacob and Jakobsson, Andreas LU
- organization
- publishing date
- 2013
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Speech enhancement, microphone arrays, beamforming, pitch estimation, DOA estimation
- host publication
- Signal and Information Processing (ChinaSIP), 2013 IEEE China Summit & International Conference on
- pages
- 5 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2013 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP)
- conference location
- Beijing, China
- conference dates
- 2013-07-06 - 2013-07-10
- external identifiers
-
- scopus:84889573855
- DOI
- 10.1109/ChinaSIP.2013.6625349
- language
- English
- LU publication?
- yes
- id
- bb1c58ac-f27e-4f06-95ea-0d02f7077c08 (old id 3991188)
- date added to LUP
- 2016-04-04 10:55:59
- date last changed
- 2022-01-29 21:03:57
@inproceedings{bb1c58ac-f27e-4f06-95ea-0d02f7077c08, abstract = {{In this paper, we give an overview of the background for, the ideas behind, and the challenges to be addressed in the project "Spatio-Temporal Filtering Methods for Enhancement and Separation of Speech Signals," which is funded by the Villum Foundation. The project aims at addressing the problem of enhancing and separating speech signals from noisy mixtures, a problem also known as the cocktail party problem. It aims at exploring new ways of solving this problem by generalizing a new class of optimal temporal filtering methods for periodic signals to multiple microphones, resulting in so-called spatio-temporal filtering methods that are controlled by two parameters, the direction-of-arrival and the fundamental frequency. These filters are optimal in that they let the signal of interest pass undistorted while everything else is attenuated as much as possible. Unlike state-of-the-art methods, they do not require knowledge of the statistics of noise and interfering speech signals, something that is especially important when dealing with non-stationary noise.}}, author = {{Christensen, Mads and Jensen, Jesper and Benesty, Jacob and Jakobsson, Andreas}}, booktitle = {{Signal and Information Processing (ChinaSIP), 2013 IEEE China Summit & International Conference on}}, keywords = {{Speech enhancement; microphone arrays; beamforming; pitch estimation; DOA estimation}}, language = {{eng}}, pages = {{303--307}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Spatio-temporal filtering methods for enhancement and separation of speech signals}}, url = {{http://dx.doi.org/10.1109/ChinaSIP.2013.6625349}}, doi = {{10.1109/ChinaSIP.2013.6625349}}, year = {{2013}}, }