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Sparse Sinusoidal Representation for Monaural Sound Separation

عنوان مقاله: Sparse Sinusoidal Representation for Monaural Sound Separation
شناسه ملی مقاله: ICEE16_114
منتشر شده در شانزدهمین کنفرانس مهندسی برق ایران در سال 1387
مشخصات نویسندگان مقاله:

Pejman Mowlaee Begzade Mahale - Department of Electrical Engineering, Amirkabir University.
Abolghasem Sayadiyan - Department of Electrical Engineering, Amirkabir University.
M Rahmati - Associate Professor at Computer Engineering Department

خلاصه مقاله:
We present a Fixed Dimension Modified Sinusoid Model (FD-MSM) for parametric analysis of all audible signals consisting of speech, music and their mixtures. Compared with previous analysis models, the proposed scheme is pitch independent as well as appropriate for commonly used clustering algorithms including Vector Quantization (VQ) or Gaussian Mixture Model (GMM) due to its fixed feature dimension which in turn results in a significant reduction in search space. Evaluating proposed FD-MSM by conducting subjective experiments, we observed that the resulting signal is perceptually indistinguishable from the original.

کلمات کلیدی:
STFT, MOS, Mel-scale, eigendecomposition

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/47612/