Name
Title | ||
|---|---|---|
Generalized independent low-rank matrix analysis using heavy-tailed distributions for blind source separation |
Abstract | ||
|---|---|---|
In this paper, statistical-model generalizations of independent low-rank matrix analysis (ILRMA) are proposed for achieving high-quality blind source separation (BSS). BSS is a crucial problem in realizing many audio applications, where the audio sources must be separated using only the observed mixture signal. Many algorithms for solving BSS have been proposed, especially in the history of independent component analysis and nonnegative matrix factorization. In particular, ILRMA can achieve the highest separation performance for music or speech mixtures, where ILRMA assumes both independence between sources and the low-rankness of time-frequency structure in each source. In this paper, we propose two extensions of the source distribution assumed in ILRMA. We introduce a heavy-tailed property by replacing the conventional Gaussian source distribution with a generalized Gaussian or Student’s t distribution. Convergence-guaranteed efficient algorithms are derived for the proposed methods, and the relationship between the generalized Gaussian and Student’s t distributions in the source model estimation is revealed. By experimental evaluation, the validity of the heavy-tailed generalizations of ILRMA is confirmed. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s13634-018-0549-5 | EURASIP Journal on Advances in Signal Processing |
Keywords | Field | DocType |
Blind audio source separation,Independent low-rank matrix analysis,Nonnegative matrix factorization,Student’s t distribution,Generalized Gaussian distribution | Matrix analysis,Computer science,Student's t-distribution,Algorithm,Gaussian,Low-rank approximation,Non-negative matrix factorization,Independent component analysis,Artificial intelligence,Blind signal separation,Machine learning,Generalized normal distribution | Journal |
Volume | Issue | ISSN |
2018 | 1 | 1687-6180 |
Citations | PageRank | References |
8 | 0.56 | 24 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daichi Kitamura | 1 | 142 | 21.21 |
| Shinichi Mogami | 2 | 21 | 2.65 |
| Yoshiki Mitsui | 3 | 8 | 0.56 |
| Norihiro Takamune | 4 | 35 | 10.18 |
| Saruwatari, H. | 5 | 652 | 90.81 |
| N. Ono | 6 | 853 | 90.18 |
| Yu Takahashi | 7 | 117 | 20.42 |
| Kazunobu Kondo | 8 | 93 | 18.13 |