Name
Title | ||
|---|---|---|
Time-frequency clustering with weighted and contextual information for convolutive blind source separation |
Abstract | ||
|---|---|---|
In this paper we investigate the use of observation weights and contextual time-frequency information for clustering-based blind source separation. Previous clustering-based approaches have successfully used clustering techniques to estimate time-frequency separation masks; however, these approaches generally disregard the structured nature of speech signals. Motivated by the homogenous behavior of speech signals, we propose to modify the established fuzzy c-means algorithm to bias the clustering results in favor of cluster membership homogeneity within localized neighborhoods in the time-frequency space. This problem can be solved by using a two-stage algorithm: firstly, the estimation of data weights to indicate the reliability of each data point, and secondly, the integration of local contextual information into the cluster update equations from neighboring time-frequency slots. The proposed algorithm is evaluated in a three-fold manner using simulated, real recordings and public benchmark data; notable improvement in source separation performance over previous clustering approaches was achieved. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/SSP.2014.6884599 | Statistical Signal Processing |
Keywords | DocType | Citations |
blind source separation,pattern clustering,speech processing,time-frequency analysis,cluster membership homogeneity,cluster update equation,clustering-based approach,clustering-based blind source separation,contextual information,contextual time-frequency information,convolutive blind source separation,data point reliability,data weight estimation,fuzzy C-means algorithm,local contextual information integration,localized neighborhood,neighboring time-frequency slot,observation weight,public benchmark data,source separation performance,speech signal homogenous behavior,speech signal structured nature,time-frequency clustering,time-frequency separation mask estimation,time-frequency space,weighted information,blind source separation,contextual information,fuzzy c-means clustering,observation weights,time-frequency masking | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ingrid Jafari | 1 | 0 | 0.34 |
| Matt Atcheson | 2 | 0 | 0.34 |
| Roberto Togneri | 3 | 814 | 48.33 |
| Sven Nordholm | 4 | 405 | 62.82 |