Monaural Speech Segregation Based on Pitch Tracking and ...

More documents

Recommendations

Info

Summary• This Model applies different mechanism todeal with resolved and unresolvedharmonics• This Model uses temporal structure tosegregate speech from mixure (Autocorrelations, Pitch Detection and AM)• The model Uses iterative Process• Good criteria for measuring performances is“ideal mask”26
My Opinion• From the results we can see goodperformance• We can use this algorithm iteratively to findless dominant pitches (more sources)• This algorithm maybe complex toimplement• This algorithm design for voiced speech27
Page 1 and 2: Monaural S
Page 3 and 4: Introduction• Speech</str
Page 5: Definitions(cont.)• Low-order har
Page 8 and 9: Model Overview(cont.)Auditory Featu
Page 10 and 11: Initial Segregation</strong
Page 12 and 13: Illustration12
Page 14 and 15: Unit Labeling• Now we compute the
Page 16 and 17: Labaling Unresolve Harmonics• The
Page 18 and 19: Final Segragation• Segments corre
Page 20 and 21: Results and Comparison• SNR Crite
Page 22 and 23: Ideal Binary Mask Criteria• Ideal
Page 24 and 25: Results24

Monaural Speech Segregation Based on Pitch Tracking and ...

Create successful ePaper yourself

Delete template?

Save as template?