作者：
Tao, LiangKwan, Hon KeungAnhui Univ
Sch Comp Sci & Technol MOE Key Lab Intelligent Comp & Signal Proc Hefei 230039 Anhui Peoples R China Univ Windsor
Dept Elect & Comp Engn Windsor ON N9B 3P4 Canada
Two-dimensional fast Gabor transform algorithms are useful for real-time applications due to the high computational complexity of the traditional 2-D complex-valued discrete Gabor transform (CDGT). This paper presents...
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Two-dimensional fast Gabor transform algorithms are useful for real-time applications due to the high computational complexity of the traditional 2-D complex-valued discrete Gabor transform (CDGT). This paper presents two block time-recursive algorithms for 2-D DHT-based real-valued discrete Gabor transform (RDGT) and its inverse transform and develops a fast parallel approach for the implementation of the two algorithms. The computational complexity of the proposed parallel approach is analyzed and compared with that of the existing 2-D CDGT algorithms. The results indicate that the proposed parallel approach is attractive for real time image processing.
As typical voice conversion methods, two spectral conversion processes have been proposed: 1) the frame-based conversion that converts spectral parameters frame by frame and 2) the trajectory-based conversion that con...
详细信息
ISBN:
(纸本)9781615673780
As typical voice conversion methods, two spectral conversion processes have been proposed: 1) the frame-based conversion that converts spectral parameters frame by frame and 2) the trajectory-based conversion that converts all spectral parameters over an utterance simultaneously. The former process is capable of real-time conversion but it sometimes causes inappropriate spectral movements. On the other hand, the latter process provides the converted spectral parameters exhibiting proper dynamic characteristics but a batch process is inevitable. To achieve the real-time conversion process considering spectral dynamic characteristics, we propose a time-recursive conversion algorithm based on maximum likelihood estimation of spectral parameter trajectory. Experimental results show that the proposed method achieves the low-delay conversion process, e.g., only one frame delay, while keeping the conversion performance comparably high to that of the conventional trajectory-based conversion.
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