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20172025
most citedLearning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks

2 citations · 3 across the 5 of their papers we have counts for

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cs.SD2019

Problem-Agnostic Speech Embeddings for Multi-Speaker Text-to-Speech with SampleRNN

David Álvarez, Santiago Pascual, Antonio Bonafonte

Text-to-speech (TTS) acoustic models map linguistic features into an acoustic representation out of which an audible waveform is generated. The latest and most natural TTS systems…

cs.SD2019

Towards Generalized Speech Enhancement with Generative Adversarial Networks

Santiago Pascual, Joan Serrà, Antonio Bonafonte

The speech enhancement task usually consists of removing additive noise or reverberation that partially mask spoken utterances, affecting their intelligibility. However, little att…

cs.SD2018

Whispered-to-voiced Alaryngeal Speech Conversion with Generative Adversarial Networks

Santiago Pascual, Antonio Bonafonte, Joan Serrà +1

Most methods of voice restoration for patients suffering from aphonia either produce whispered or monotone speech. Apart from intelligibility, this type of speech lacks expressiven…

cs.SD2018

Self-Attention Linguistic-Acoustic Decoder

Santiago Pascual, Antonio Bonafonte, Joan Serrà

The conversion from text to speech relies on the accurate mapping from linguistic to acoustic symbol sequences, for which current practice employs recurrent statistical models like…

cs.SD2017

Language and Noise Transfer in Speech Enhancement Generative Adversarial Network

Santiago Pascual, Maruchan Park, Joan Serrà +2

Speech enhancement deep learning systems usually require large amounts of training data to operate in broad conditions or real applications. This makes the adaptability of those sy…