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Block-wise training for i-vector | IEEE Conference Publication | IEEE Xplore
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Block-wise training for i-vector


Abstract:

We propose a fast block-wise and parallel training approach to train i-vector systems. This approach divides the loading matrix into groups according to components or aco...Show More

Abstract:

We propose a fast block-wise and parallel training approach to train i-vector systems. This approach divides the loading matrix into groups according to components or acoustic feature dimensions and trains the loading matrices of these groups independently and in parallel. These individually trained block matrices can be combined to approximate the original loading matrix, or used to derive independent i-vectors. We tested the block-wise training on speaker verification tasks based on the NIST SRE data and found that it can substantially speed up the training while retaining the quality of the resulting i-vectors.
Date of Conference: 09-13 July 2014
Date Added to IEEE Xplore: 04 September 2014
ISBN Information:
Conference Location: Xi'an, China

References

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