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Found 5 papers, 4 papers with code
Deep Speech Synthesis from MRI-Based Articulatory Representations
Finally, through a series of ablations, we show that the proposed MRI representation is more comprehensive than EMA and identify the most suitable MRI feature subset for articulatory synthesis.
Speaker-Independent Acoustic-to-Articulatory Speech Inversion
To build speech processing methods that can handle speech as naturally as humans, researchers have explored multiple ways of building an invertible mapping from speech to an interpretable space.
Articulatory Representation Learning Via Joint Factor Analysis and Neural Matrix Factorization
In this work, we propose a novel articulatory representation decomposition algorithm that takes the advantage of guided factor analysis to derive the articulatory-specific factors and factor scores.
Deep Speech Synthesis from Articulatory Representations
In the articulatory synthesis task, speech is synthesized from input features containing information about the physical behavior of the human vocal tract.
Deep Neural Convolutive Matrix Factorization for Articulatory Representation Decomposition
Most of the research on data-driven speech representation learning has focused on raw audios in an end-to-end manner, paying little attention to their internal phonological or gestural structure.
