1. SINGLE CHANNEL SPEECH MUSIC SEPARATION USING NONNEGATIVE MATRIXFACTORIZATION AND SPECTRAL MASKS
Emad M. Grais
Hakan Erdogan
17th International Conference on Digital Signal Processing,2011
Jain-De,Lee

2. Outline INTRODUCTION NON-NEGATIVE MATRIX FACTORIZATION
SIGNAL SEPARATION AND MASKING
EXPERIMENTS AND DISCUSSION
CONCLUSION

3. Introduction There are two main stages of this work
Training stage
Separation stage
Using NMF with different types of masks to improve the separation process
The separation process faster
NMF with fewer iterations

4. Introduction Problem formulation X = S + M
The observe a signal x(t) ,which is the mixture of two sources s(t) and m(t)
Assume the sources have the same phase angle as the mixed
Where (t , f) be the STFT of x(t)
X = S + M

5. Non-negative Matrix Factorization
Non-negative matrix factorization algorithm
Minimization problem
Different cost functions C of NMF
Euclidean distance
KL divergence
subject to elements of B,W≧0

6. Non-negative Matrix Factorization
The magnitude spectrogram S and M are calculated by NMF
Larger number of basis vectors
Lower approximation error
Redundant set of basis
Require more computation time

7. Signal Separation and Masking
The NMF is used decompose the magnitude spectrogram matrix X
The initial spectrograms estimates for speech and music signals are respectively calculated as follows
Where WS and WM are submatrices in matrix W

8. Signal Separation and Masking
Use the initial estimated spectrograms and to build a mask as follows
Source signals reconstruction
Where 1 is a matrix of ones
is element-wise multiplication

9. Signal Separation and Masking
The value of the mask versus the linear ratio for different values of p

10. Signal Separation and Masking
Two specific values of p correspond to special masks
Wiener filter(soft mask)
Hard mask

11. Experiments and Discussion
Simulation
16kHz sampling rate
Speech
Training speech data-540 short utterances
Testing speech data-20 utterances
Music
38 pieces for training
one piece for testing
Hamming window-512 point
FFT size-512 point

12. Experiments and Discussion

13. Experiments and Discussion

14. Experiments and Discussion

15. Experiments and Discussion

16. Conclusion
The family of masks have a parameter to control the saturation level
The proposed algorithm gives better results and facilitates to speed up the separation process