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Found 9 papers, 5 papers with code
Toward Joint Language Modeling for Speech Units and Text
However, in the field of language modeling, very little effort has been made to model them jointly.
Few-Shot Spoken Language Understanding via Joint Speech-Text Models
Recent work on speech representation models jointly pre-trained with text has demonstrated the potential of improving speech representations by encoding speech and text in a shared space.
AV2Wav: Diffusion-Based Re-synthesis from Continuous Self-supervised Features for Audio-Visual Speech Enhancement
In this work, we introduce AV2Wav, a resynthesis-based audio-visual speech enhancement approach that can generate clean speech despite the challenges of real-world training data.
What Do Self-Supervised Speech Models Know About Words?
Many self-supervised speech models (S3Ms) have been introduced over the last few years, improving performance and data efficiency on various speech tasks.
Voice Filter: Few-shot text-to-speech speaker adaptation using voice conversion as a post-processing module
It uses voice conversion (VC) as a post-processing module appended to a pre-existing high-quality TTS system and marks a conceptual shift in the existing TTS paradigm, framing the few-shot TTS problem as a VC task.
S2VC: A Framework for Any-to-Any Voice Conversion with Self-Supervised Pretrained Representations
AUTOVC used dvector to extract speaker information, and self-supervised learning (SSL) features like wav2vec 2. 0 is used in FragmentVC to extract the phonetic content information.
Investigating on Incorporating Pretrained and Learnable Speaker Representations for Multi-Speaker Multi-Style Text-to-Speech
The few-shot multi-speaker multi-style voice cloning task is to synthesize utterances with voice and speaking style similar to a reference speaker given only a few reference samples.
Hierarchical Prosody Modeling for Non-Autoregressive Speech Synthesis
Prosody modeling is an essential component in modern text-to-speech (TTS) frameworks.
FragmentVC: Any-to-Any Voice Conversion by End-to-End Extracting and Fusing Fine-Grained Voice Fragments With Attention
Any-to-any voice conversion aims to convert the voice from and to any speakers even unseen during training, which is much more challenging compared to one-to-one or many-to-many tasks, but much more attractive in real-world scenarios.
