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20182026
most citedGeneralizing AUC Optimization to Multiclass Classification for Audio Segmentation With Limited Training Data

19 citations · 42 across the 11 of their papers we have counts for

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cs.SD2024

Audio-Visual Speaker Diarization: Current Databases, Approaches and Challenges

Victoria Mingote, Alfonso Ortega, Antonio Miguel +1

Nowadays, the large amount of audio-visual content available has fostered the need to develop new robust automatic speaker diarization systems to analyse and characterise it. This…

cs.SD202119 cited

Generalizing AUC Optimization to Multiclass Classification for Audio Segmentation With Limited Training Data

Pablo Gimeno, Victoria Mingote, Alfonso Ortega +2

Area under the ROC curve (AUC) optimisation techniques developed for neural networks have recently demonstrated their capabilities in different audio and speech related tasks. Howe…

cs.SD201915 cited

Deep Speech Enhancement for Reverberated and Noisy Signals using Wide Residual Networks

Dayana Ribas, Jorge Llombart, Antonio Miguel +1

This paper proposes a deep speech enhancement method which exploits the high potential of residual connections in a wide neural network architecture, a topology known as Wide Resid…

cs.SD2019

Optimization of the Area Under the ROC Curve using Neural Network Supervectors for Text-Dependent Speaker Verification

Victoria Mingote, Antonio Miguel, Alfonso Ortega +1

This paper explores two techniques to improve the performance of text-dependent speaker verification systems based on deep neural networks. Firstly, we propose a general alignment…

cs.SD2018

Differentiable Supervector Extraction for Encoding Speaker and Phrase Information in Text Dependent Speaker Verification

Victoria Mingote, Antonio Miguel, Alfonso Ortega +1

In this paper, we propose a new differentiable neural network alignment mechanism for text-dependent speaker verification which uses alignment models to produce a supervector repre…