3 citations · 8 across the 13 of their papers we have counts for
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An Efficient End-to-End Approach to Noise Invariant Speech Features via Multi-Task Learning
Heitor R. Guimarães, Arthur Pimentel, Anderson R. Avila +3
Self-supervised speech representation learning enables the extraction of meaningful features from raw waveforms. These features can then be efficiently used across multiple downstr…
On the Transferability of Whisper-based Representations for "In-the-Wild" Cross-Task Downstream Speech Applications
Vamsikrishna Chemudupati, Marzieh Tahaei, Heitor Guimaraes +5
Large self-supervised pre-trained speech models have achieved remarkable success across various speech-processing tasks. The self-supervised training of these models leads to unive…
RobustDistiller: Compressing Universal Speech Representations for Enhanced Environment Robustness
Heitor R. Guimarães, Arthur Pimentel, Anderson R. Avila +3
Self-supervised speech pre-training enables deep neural network models to capture meaningful and disentangled factors from raw waveform signals. The learned universal speech repres…