A Unified Joint Model to Deal With Nuisance Variabilities in the i-Vector Space.

IEEE/ACM Transactions on Audio, Speech, and Language Processing(2018)

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摘要
The past decade has witnessed a significant improvement in speaker recognition (SR) technology in terms of performance with the introduction of the i-vectors framework. Despite these advances, the performance of SR systems considerably suffers in the presence of acoustic nuisances and variabilities. In this paper, we develop a data-driven nuisance compensation technique in the i-vector space witho...
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关键词
Additive noise,Speech,Acoustics,Speech processing,Computational modeling,Training,Robustness
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