Antonio Miguel — accepted AI-conference papers

2021

Memory Layers with Multi-Head Attention Mechanisms for Text-Dependent Speaker Verification

Victoria Mingote, Antonio Miguel, Alfonso Ortega Giménez, Eduardo Lleida

ICASSP 2021accepted

In this paper, we explore an approach based on memory layers and multi-head attention mechanisms to improve in an efficient way the performance of text-dependent speaker verification (SV) systems. The most extended SV systems based on Deep Neural Networks (DNN) extract the embedding of the utterance…

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2020

Knowledge Distillation and Random Erasing Data Augmentation for Text-Dependent Speaker Verification

Victoria Mingote, Antonio Miguel, Dayana Ribas, Alfonso Ortega Giménez, Eduardo Lleida

ICASSP 2020accepted

This paper explores the Knowledge Distillation (KD) approach and a data augmentation technique to improve the generalization ability and robustness of text-dependent speaker verification (SV) systems. The KD method consists of two neural networks, known as Teacher and Student, where the student is t…

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