| Paper: | SS-6.3 | ||
| Session: | Convolutive Blind Source Separation for Speech and Audio Signals | ||
| Time: | Wednesday, May 19, 16:10 - 16:30 | ||
| Presentation: | Special Session Lecture | ||
| Topic: | Special Sessions: Convolutive Blind Source Separation for Speech and Audio Signals | ||
| Title: | CONVOLUTIVE BLIND SOURCE SEPARATION FOR MORE THAN TWO SOURCES IN THE FREQUENCY DOMAIN | ||
| Authors: | Hiroshi Sawada; NTT Corporation | ||
| Ryo Mukai; NTT Corporation | |||
| Shoko Araki; NTT Corporation | |||
| Shoji Makino; NTT Corporation | |||
| Abstract: | Blind source separation (BSS) for convolutive mixtures can be efficiently achieved in the frequency domain, where independent component analysis is performed separately in each frequency bin. However, frequency-domain BSS involves a permutation problem, which is well known as a difficult problem, especially when the number of sources is large. This paper presents a method for solving the permutation problem, which works well even for many sources. The successful solution for the permutation problem highlights another problem with frequency-domain BSS that arises from the circularity of discrete frequency representation. This paper discusses the phenomena of the problem and presents a method for solving it. With these two methods, we can separate many sources with a practical execution time. Moreover, real-time processing is currently possible for up to three sources with our implementation. | ||
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