Abstract

There is frequent noise that affects the performance of voice recog-nition and speaker recognition algorithms in a real-world envi-ronment. For voice and speaker recognition systems to be more robust, these noises must not interfere in a harmful way, causingerrors in understanding commands. To evaluate signal degradationand speaker recognition when exposed to real-world environments,we explore a reverberation noise simulation environment usinga specific library in this work. We tested a speaker recognition model with i-vectors and Probabilistic Linear Discriminant Analy-sis (PLDA). We have analyzed the impact of noise in conjunction with reverberation on its error rate. Results based on Monte Carlosimulation showed that, for the tested cases, the noise set withreverberation worsened the recognition rate by up to 24,43%.

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