Two-stage iterative Procrustes match algorithm and its application for VQ-based verification

Richeng Tan; Jing Li

doi:10.1117/12.2523293

15 March 2019 Two-stage iterative Procrustes match algorithm and its application for VQ-based verification

Richeng Tan, Jing Li

Proceedings Volume 11041, Eleventh International Conference on Machine Vision (ICMV 2018); 110411F (2019) https://doi.org/10.1117/12.2523293
Event: Eleventh International Conference on Machine Vision (ICMV 2018), 2018, Munich, Germany

Abstract

In the past decades, Vector Quantization (VQ) model has been very popular across different pattern recognition areas, especially for feature-based tasks. However, the classification or regression performance of VQ-based systems always confronts the feature mismatch problem, which will heavily affect the performance of them. In this paper, we propose a two-stage iterative Procrustes algorithm (TIPM) to address the feature mismatch problem for VQ-based applications. At the first stage, the algorithm will remove mismatched feature vector pairs for a pair of input feature sets. Then, the second stage will collect those correct matched feature pairs that were discarded during the first stage. To evaluate the effectiveness of the proposed TIPM algorithm, speaker verification is used as the case study in this paper. The experiments were conducted on the TIMIT database and the results show that TIPM can improve VQ-based speaker verification performance clean condition and all noisy conditions.

Citation Download Citation

Richeng Tan and Jing Li "Two-stage iterative Procrustes match algorithm and its application for VQ-based verification", Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110411F (15 March 2019); https://doi.org/10.1117/12.2523293

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