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Found 11 papers, 5 papers with code
VoxGenesis: Unsupervised Discovery of Latent Speaker Manifold for Speech Synthesis
This forces the model to learn a speaker distribution disentangled from the semantic content.
Towards Hierarchical Spoken Language Dysfluency Modeling
Speech disfluency modeling is the bottleneck for both speech therapy and language learning.
Unconstrained Dysfluency Modeling for Dysfluent Speech Transcription and Detection
Dysfluent speech modeling requires time-accurate and silence-aware transcription at both the word-level and phonetic-level.
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.
AV-data2vec: Self-supervised Learning of Audio-Visual Speech Representations with Contextualized Target Representations
Self-supervision has shown great potential for audio-visual speech recognition by vastly reducing the amount of labeled data required to build good systems.
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.
UTTS: Unsupervised TTS with Conditional Disentangled Sequential Variational Auto-encoder
We leverage recent advancements in self-supervised speech representation learning as well as speech synthesis front-end techniques for system development.
Towards Improved Zero-shot Voice Conversion with Conditional DSVAE
In our experiment on the VCTK dataset, we demonstrate that content embeddings derived from the conditional DSVAE overcome the randomness and achieve a much better phoneme classification accuracy, a stabilized vocalization and a better zero-shot VC performance compared with the competitive DSVAE baseline.
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.
Robust Disentangled Variational Speech Representation Learning for Zero-shot Voice Conversion
A zero-shot voice conversion is performed by feeding an arbitrary speaker embedding and content embeddings to the VAE decoder.
Masked Proxy Loss For Text-Independent Speaker Verification
We further propose Multinomial Masked Proxy (MMP) loss to leverage the hardness of speaker pairs.
