163 citations · 259 across the 8 of their papers we have counts for
5 papers · 1 filter
VioLA: Unified Codec Language Models for Speech Recognition, Synthesis, and Translation
Tianrui Wang, Long Zhou, Ziqiang Zhang +6
Recent research shows a big convergence in model architecture, training objectives, and inference methods across various tasks for different modalities. In this paper, we propose V…
Speak Foreign Languages with Your Own Voice: Cross-Lingual Neural Codec Language Modeling
Ziqiang Zhang, Long Zhou, Chengyi Wang +10
We propose a cross-lingual neural codec language model, VALL-E X, for cross-lingual speech synthesis. Specifically, we extend VALL-E and train a multi-lingual conditional codec lan…
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
Chengyi Wang, Sanyuan Chen, Yu Wu +10
We introduce a language modeling approach for text to speech synthesis (TTS). Specifically, we train a neural codec language model (called Vall-E) using discrete codes derived from…
SpeechUT: Bridging Speech and Text with Hidden-Unit for Encoder-Decoder Based Speech-Text Pre-training
Ziqiang Zhang, Long Zhou, Junyi Ao +4
The rapid development of single-modal pre-training has prompted researchers to pay more attention to cross-modal pre-training methods. In this paper, we propose a unified-modal spe…
SpeechLM: Enhanced Speech Pre-Training with Unpaired Textual Data
Ziqiang Zhang, Sanyuan Chen, Long Zhou +8
How to boost speech pre-training with textual data is an unsolved problem due to the fact that speech and text are very different modalities with distinct characteristics. In this…