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arXiv · 1603.09460

System Combination for Short Utterance Speaker Recognition

Lantian Li·Dong Wang·Xiaodong Zhang·Thomas Fang Zheng·Panshi Jin
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Abstract

For text-independent short-utterance speaker recognition (SUSR), the performance often degrades dramatically. This paper presents a combination approach to the SUSR tasks with two phonetic-aware systems: one is the DNN-based i-vector system and the other is our recently proposed subregion-based GMM-UBM system. The former employs phone posteriors to construct an i-vector model in which the shared statistics offers stronger robustness against limited test data, while the latter establishes a phone-dependent GMM-UBM system which represents speaker characteristics with more details. A score-level fusion is implemented to integrate the respective advantages from the two systems. Experimental results show that for the text-independent SUSR task, both the DNN-based i-vector system and the subregion-based GMM-UBM system outperform their respective baselines, and the score-level system combination delivers performance improvement.

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Lantian Li, Dong Wang, Xiaodong Zhang, Thomas Fang Zheng, Panshi Jin. 2016-03-31. System Combination for Short Utterance Speaker Recognition. https://arxiv.org/abs/1603.09460

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