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Dayana Ribas

2 accepted papers

2020

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

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…

Cited by 0Source ↗Scholar ↗
2019

An Improved Uncertainty Propagation Method for Robust I-vector Based Speaker Recognition

ICASSP 2019accepted

The performance of automatic speaker recognition systems degrades when facing distorted speech data containing additive noise and/or reverberation. Statistical uncertainty propagation has been introduced as a promising paradigm to address this challenge. So far, different uncertainty propagation met…

Cited by 0Source ↗Scholar ↗